Inside-out tracking - Revision history

VRWIKI: light house tracking is a form of inside out tracking, just because it uses external hardware does not mean its inside out

2025-10-06T18:40:42Z

light house tracking is a form of inside out tracking, just because it uses external hardware does not mean its inside out

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	* '''Pico Neo''' series (for example Pico Neo 3, Pico 4).		* '''Pico Neo''' series (for example Pico Neo 3, Pico 4).
	* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets using [[HPU (Holographic Processing Unit)\|HPUs]] for processing).		* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets using [[HPU (Holographic Processing Unit)\|HPUs]] for processing).
	* '''[[Valve Index]]''' (~~Uses inside-out cameras primarily for passthrough view, room setup scanning, and potentially some experimental features, but relies on [[Lighthouse]] (outside-in~~) ~~for its primary HMD and controller tracking).~~		* '''[[Valve Index]]''' (SteamVR Base Station 2.0)
	* '''[[PlayStation VR2]]''' (Uses inside-out cameras for HMD and controller tracking).		* '''[[PlayStation VR2]]''' (Uses inside-out cameras for HMD and controller tracking).
	* '''[[Apple Vision Pro]]''' (MR headset).		* '''[[Apple Vision Pro]]''' (MR headset).

RealEditor: /* Examples of Devices and Platforms Using Inside-out Tracking */ Wii only used IR for pointing

2025-07-02T20:11:04Z

Examples of Devices and Platforms Using Inside-out Tracking: Wii only used IR for pointing

← Older revision		Revision as of 20:11, 2 July 2025
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	* '''[[Lenovo Mirage Solo]]''' (Used Google's [[WorldSense]] tracking).		* '''[[Lenovo Mirage Solo]]''' (Used Google's [[WorldSense]] tracking).
	* '''[[Magic Leap]]''' 1 and 2.		* '''[[Magic Leap]]''' 1 and 2.
	* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing~~/orientation~~).		* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing).

	==References==		==References==

Xinreality: Text replacement - "e.g.," to "for example"

2025-04-29T04:22:53Z

Text replacement - "e.g.," to "for example"

Xinreality at 10:50, 25 April 2025

2025-04-25T10:50:54Z

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	{{main\|Markerless inside-out tracking}}		{{main\|Markerless inside-out tracking}}
	This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.		This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.
	* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated [[algorithms]], often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (e.g., fast movements, poor lighting).~~<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>~~<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated [[algorithms]], often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (e.g., fast movements, poor lighting).<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.		* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.

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	<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref>		<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref>
	<ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>		<ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>
	~~<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>~~
	<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	</references>		</references>

	[[Category:Terms]] [[Category:Technical Terms]] [[Category:Tracking Technology]]		[[Category:Terms]] [[Category:Technical Terms]] [[Category:Tracking Technology]]

Xinreality at 00:40, 24 April 2025

2025-04-24T00:40:22Z

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			{{see also\|Terms\|Technical Terms}}
	{{see also\|Markerless inside-out tracking‎\|Positional tracking\|Outside-in tracking}}		{{see also\|Markerless inside-out tracking‎\|Positional tracking\|Outside-in tracking}}
	==Introduction==		==Introduction==

Xinreality: /* Examples of Devices and Platforms Using Inside-out Tracking */

2025-04-24T00:39:54Z

Examples of Devices and Platforms Using Inside-out Tracking

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	==Examples of Devices and Platforms Using Inside-out Tracking==		==Examples of Devices and Platforms Using Inside-out Tracking==
	Many modern VR/AR/MR systems utilize markerless inside-out tracking:		Many modern VR/AR/MR systems utilize markerless inside-out tracking:
	* '''[[Meta Quest]] series''' ([[Oculus Quest]], Quest 2, Quest 3, [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.		* '''[[Meta Quest]] series''' ([[Oculus Quest]], [[Quest 2]], [[Quest 3]], [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.
	* '''[[Oculus Rift S]]''' - Also used Oculus Insight.		* '''[[Oculus Rift S]]''' - Also used Oculus Insight.
	* '''[[Windows Mixed Reality]]''' platform headsets (e.g., [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).		* '''[[Windows Mixed Reality]]''' platform headsets (e.g., [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).

Xinreality at 00:26, 24 April 2025

2025-04-24T00:26:17Z

← Older revision		Revision as of 00:26, 24 April 2025
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	{{see also\|Markerless inside-out tracking‎\|Positional tracking\|Outside-in tracking}}		{{see also\|Markerless inside-out tracking‎\|Positional tracking\|Outside-in tracking}}
	[[File:Acer mixed reality headset inside-out.png\|thumb\|Figure 1. A Windows Mixed Reality headset, an example of an HMD using markerless inside-out tracking via cameras visible on the front (image: www.wareable.com)]]		==Introduction==
			[[File:Acer mixed reality headset inside-out.png\|thumb\|Figure 1. A [[Windows Mixed Reality headset]], an example of an HMD using markerless inside-out tracking via cameras visible on the front (image: www.wareable.com)]]

	~~'''~~Inside-out tracking~~'''~~ is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.		[[Inside-out tracking]] is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.

	It contrasts with [[outside-in tracking]], where external sensors (e.g., cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently [[egocentric]].<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>		It contrasts with [[outside-in tracking]], where external sensors (e.g., cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently [[egocentric]].<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>

	== How it Works ==		==How it Works==
	An inside-out tracking system observes the external world from the perspective of the device being tracked. As the device moves, the sensors detect changes relative to the environment, allowing the system to calculate the device's updated position and orientation ([[6DoF\|six degrees of freedom]] - 3 translational, 3 rotational). This calculation typically happens in real-time, allowing the virtual environment to respond accordingly.		An inside-out tracking system observes the external world from the perspective of the device being tracked. As the device moves, the sensors detect changes relative to the environment, allowing the system to calculate the device's updated position and orientation ([[6DoF\|six degrees of freedom]] - 3 translational, 3 rotational). This calculation typically happens in real-time, allowing the virtual environment to respond accordingly.

	There are two main approaches:		There are two main approaches:

	=== Marker-based Inside-out Tracking ===		===Marker-based Inside-out Tracking===
			[[File:F2Ak4iE.jpg\|thumbnail\|Figure 2. Early [[Lighthouse]] prototype, an inside-out tracking system with 2-dimensional barcodes as [[fiducial markers]].]]
	This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.		This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.
	* '''Mechanism:''' Cameras or other [[optical sensor]]s on the device identify the known patterns or shapes of the fiducial markers (e.g., QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>		* '''Mechanism:''' Cameras or other [[optical sensor]]s on the device identify the known patterns or shapes of the fiducial markers (e.g., QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>
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	* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).		* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).

	=== Markerless Inside-out Tracking ===		===Markerless Inside-out Tracking===
	{{main\|Markerless inside-out tracking}}		{{main\|Markerless inside-out tracking}}
	This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.		This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.
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	* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.		* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.

	== Advantages ==		==Advantages==
	* '''Simpler Setup:''' No need to install external sensors, base stations, or markers in the room.		* '''Simpler Setup:''' No need to install external sensors, base stations, or markers in the room.
	* '''Portability:''' Systems are often self-contained, making them easier to move between different locations.		* '''Portability:''' Systems are often self-contained, making them easier to move between different locations.
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	* '''Lower System Cost (Potentially):''' Eliminating external tracking hardware can reduce the overall cost of the VR system, although it increases the complexity and [[computational cost]] on the headset itself.		* '''Lower System Cost (Potentially):''' Eliminating external tracking hardware can reduce the overall cost of the VR system, although it increases the complexity and [[computational cost]] on the headset itself.

	== Disadvantages ==		==Disadvantages==
	* '''Controller [[Occlusion]]:''' Tracking of controllers can be lost if they move outside the [[field of view]] of the HMD's cameras (e.g., behind the user's back, too close to the HMD). Predictive algorithms using IMU data help mitigate this for short periods.		* '''Controller [[Occlusion]]:''' Tracking of controllers can be lost if they move outside the [[field of view]] of the HMD's cameras (e.g., behind the user's back, too close to the HMD). Predictive algorithms using IMU data help mitigate this for short periods.
	* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (e.g., blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.		* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (e.g., blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.
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	* '''Initialization:''' The system needs to initialize and potentially map a new area before tracking becomes fully stable.		* '''Initialization:''' The system needs to initialize and potentially map a new area before tracking becomes fully stable.

	== Examples of Devices and Platforms Using Inside-out Tracking ==		==Examples of Devices and Platforms Using Inside-out Tracking==
	Many modern VR/AR/MR systems utilize markerless inside-out tracking:		Many modern VR/AR/MR systems utilize markerless inside-out tracking:
	* '''[[Meta Quest]] series''' ([[Oculus Quest]], Quest 2, Quest 3, [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.		* '''[[Meta Quest]] series''' ([[Oculus Quest]], Quest 2, Quest 3, [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.
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	* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing/orientation).		* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing/orientation).

	~~[[Category:Terms]] [[Category:Technical Terms]] [[Category:Tracking Technology]]~~		==References==

	== References ==
	<references>		<references>
	<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref>		<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref>
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	<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	</references>		</references>

			[[Category:Terms]] [[Category:Technical Terms]] [[Category:Tracking Technology]]

Xinreality at 00:24, 24 April 2025

2025-04-24T00:24:35Z

← Older revision		Revision as of 00:24, 24 April 2025
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	<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>		<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>
	<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	<ref name=”Langley2017”> Langley, H. (2017). Inside-out v Outside-in: How VR tracking works, and how it's going to change. Retrieved from https://www.wareable.com/vr/inside-out-vs-outside-in-vr-tracking-343</ref> {{comment\|Note: Supports advantages/disadvantages context}}
	~~<ref name=”ARVRTips2020”> AR/VR Tips (2020). VR Headset Comparison. Retrieved from https://arvrtips.com/vr-headset-comparison-tool/</ref> {{comment\|Note: Potentially supports device examples}}~~
	</references>		</references>

Xinreality at 00:15, 24 April 2025

2025-04-24T00:15:51Z

Xinreality at 00:14, 24 April 2025

2025-04-24T00:14:47Z

Show changes

← Older revision		Revision as of 04:22, 29 April 2025
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	[[Inside-out tracking]] is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.		[[Inside-out tracking]] is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.

	It contrasts with [[outside-in tracking]], where external sensors (~~e.g.,~~ cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently [[egocentric]].<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>		It contrasts with [[outside-in tracking]], where external sensors (for example cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently [[egocentric]].<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>

	==How it Works==		==How it Works==
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	[[File:F2Ak4iE.jpg\|thumbnail\|Figure 2. Early [[Lighthouse]] prototype, an inside-out tracking system with 2-dimensional barcodes as [[fiducial markers]].]]		[[File:F2Ak4iE.jpg\|thumbnail\|Figure 2. Early [[Lighthouse]] prototype, an inside-out tracking system with 2-dimensional barcodes as [[fiducial markers]].]]
	This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.		This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.
	* '''Mechanism:''' Cameras or other [[optical sensor]]s on the device identify the known patterns or shapes of the fiducial markers (~~e.g.,~~ QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>		* '''Mechanism:''' Cameras or other [[optical sensor]]s on the device identify the known patterns or shapes of the fiducial markers (for example QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>
	* '''Limitations:''' Tracking only functions when the markers are within the sensor's [[field of view]] and are not occluded. Requires setup of the environment with markers.		* '''Limitations:''' Tracking only functions when the markers are within the sensor's [[field of view]] and are not occluded. Requires setup of the environment with markers.
	* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).		* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).
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	{{main\|Markerless inside-out tracking}}		{{main\|Markerless inside-out tracking}}
	This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.		This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.
	* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated [[algorithms]], often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (~~e.g.,~~ fast movements, poor lighting).<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated [[algorithms]], often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (for example fast movements, poor lighting).<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.		* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.

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	==Disadvantages==		==Disadvantages==
	* '''Controller [[Occlusion]]:''' Tracking of controllers can be lost if they move outside the [[field of view]] of the HMD's cameras (~~e.g.,~~ behind the user's back, too close to the HMD). Predictive algorithms using IMU data help mitigate this for short periods.		* '''Controller [[Occlusion]]:''' Tracking of controllers can be lost if they move outside the [[field of view]] of the HMD's cameras (for example behind the user's back, too close to the HMD). Predictive algorithms using IMU data help mitigate this for short periods.
	* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (~~e.g.,~~ blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.		* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (for example blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.
	* '''Computational Load:''' Processing sensor data and running tracking algorithms (especially SLAM/VIO) requires significant processing power on the device itself (HMD or connected computer), potentially impacting battery life or requiring more powerful onboard processors.		* '''Computational Load:''' Processing sensor data and running tracking algorithms (especially SLAM/VIO) requires significant processing power on the device itself (HMD or connected computer), potentially impacting battery life or requiring more powerful onboard processors.
	* '''Drift:''' While modern systems are robust, markerless tracking can sometimes accumulate small positional errors over time (drift), potentially requiring occasional recalibration or re-localization, although environment mapping helps significantly.		* '''Drift:''' While modern systems are robust, markerless tracking can sometimes accumulate small positional errors over time (drift), potentially requiring occasional recalibration or re-localization, although environment mapping helps significantly.
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	* '''[[Meta Quest]] series''' ([[Oculus Quest]], [[Quest 2]], [[Quest 3]], [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.		* '''[[Meta Quest]] series''' ([[Oculus Quest]], [[Quest 2]], [[Quest 3]], [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.
	* '''[[Oculus Rift S]]''' - Also used Oculus Insight.		* '''[[Oculus Rift S]]''' - Also used Oculus Insight.
	* '''[[Windows Mixed Reality]]''' platform headsets (~~e.g.,~~ [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).		* '''[[Windows Mixed Reality]]''' platform headsets (for example [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).
	* '''[[HTC Vive Cosmos]]''' (with standard faceplate), '''[[HTC Vive Focus]]''' series, '''[[HTC Vive XR Elite]]'''.		* '''[[HTC Vive Cosmos]]''' (with standard faceplate), '''[[HTC Vive Focus]]''' series, '''[[HTC Vive XR Elite]]'''.
	* '''Pico Neo''' series (~~e.g.,~~ Pico Neo 3, Pico 4).		* '''Pico Neo''' series (for example Pico Neo 3, Pico 4).
	* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets using [[HPU (Holographic Processing Unit)\|HPUs]] for processing).		* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets using [[HPU (Holographic Processing Unit)\|HPUs]] for processing).
	* '''[[Valve Index]]''' (Uses inside-out cameras primarily for passthrough view, room setup scanning, and potentially some experimental features, but relies on [[Lighthouse]] (outside-in) for its primary HMD and controller tracking).		* '''[[Valve Index]]''' (Uses inside-out cameras primarily for passthrough view, room setup scanning, and potentially some experimental features, but relies on [[Lighthouse]] (outside-in) for its primary HMD and controller tracking).

← Older revision		Revision as of 00:15, 24 April 2025
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	'''Inside-out tracking''' is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.		'''Inside-out tracking''' is a method of [[positional tracking]] commonly used in [[virtual reality]] (VR), [[augmented reality]] (AR), and [[mixed reality]] (MR) technologies. It enables devices like [[head-mounted display\|head-mounted displays]] (HMDs) and [[motion controller]]s to determine their position and orientation in 3D space by using [[sensor]]s located on the device itself, looking outward at the surrounding environment.

	It contrasts with [[outside-in tracking]], where external sensors (e.g., cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently egocentric.<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>		It contrasts with [[outside-in tracking]], where external sensors (e.g., cameras or laser emitters) are placed in the environment to track sensors or markers located on the HMD or controllers. In inside-out tracking, the "eyes" (cameras or other sensors) are on the moving object, making the system inherently [[egocentric]].<ref name=”Ribo2001”> Ribo, M., Pinz, A. and Fuhrmann, A.L. (2001). A new optical tracking system for virtual and augmented reality applications. Instrumentation and Measurement Technology Conference Proceedings</ref><ref name=”Boger2014InOut”> Boger, Y. (2014). Positional tracking: "Outside-in" vs. "Inside-out.” Retrieved from http://vrguy.blogspot.pt/2014/08/positional-tracking-outside-in-vs.html</ref>

	== How it Works ==		== How it Works ==
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	=== Marker-based Inside-out Tracking ===		=== Marker-based Inside-out Tracking ===
	This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.		This approach relies on placing artificial markers, known as [[fiducial markers]], in the environment. The sensors on the tracked device are designed to detect these specific markers.
	* '''Mechanism:''' Cameras or other optical ~~sensors~~ on the device identify the known patterns or shapes of the fiducial markers (e.g., QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>		* '''Mechanism:''' Cameras or other [[optical sensor]]s on the device identify the known patterns or shapes of the fiducial markers (e.g., QR codes, specific geometric patterns, [[infra-red\|infrared]] (IR) LEDs). By analyzing the position, size, and orientation of these markers in the sensor's view, the system can calculate the device's pose relative to them.<ref name=”Ishii2010”> Ishii, K. (2010). Augmented Reality: Fundamentals and nuclear related applications. Nuclear Safety and Simulation, 1(1)</ref><ref name=”Mehling2006”> Mehling, M. (2006). Implementation of a Low Cost Marker Based Infrared Optical Tracking System. PhD thesis, Fachhochschule Stuttgart</ref>
	* '''Limitations:''' Tracking only functions when the markers are within the sensor's [[field of view]] and are not occluded. Requires setup of the environment with markers.		* '''Limitations:''' Tracking only functions when the markers are within the sensor's [[field of view]] and are not occluded. Requires setup of the environment with markers.
	* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).		* '''Example Concept:''' While not typically used for modern VR HMDs, the [[Nintendo Wii Remote]] utilizes a form of marker-based inside-out tracking. The IR camera in the remote tracks the position of IR LEDs located in the stationary Sensor Bar to determine where the remote is pointing (though primarily for orientation and relative pointing, not full 6DoF positional tracking).
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	{{main\|Markerless inside-out tracking}}		{{main\|Markerless inside-out tracking}}
	This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.		This is the most common approach used in modern standalone VR/MR headsets. It uses [[computer vision]] techniques to track the device's position based on recognizing natural features in the surrounding environment, without requiring any artificial markers.
	* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated algorithms, often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (e.g., fast movements, poor lighting).<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref><ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		* '''Mechanism:''' Cameras on the HMD capture video of the environment. Sophisticated [[algorithms]], often involving [[SLAM]] (Simultaneous Localization and Mapping) or [[VIO]] (Visual-Inertial Odometry), identify and track distinct features (corners, edges, textures) in the environment. As the headset moves, the system tracks how these features move across the cameras' views to calculate the device's motion. Data from onboard [[IMU\|Inertial Measurement Units]] ([[accelerometer]]s and [[gyroscope]]s) is typically fused with the visual data. The IMU provides high-frequency motion data and helps predict position during moments when visual tracking is temporarily lost (e.g., fast movements, poor lighting).<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref><ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	* '''Environment Mapping:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.		* '''[[Environment mapping\|Environment Mapping]]:''' SLAM-based systems often create and update a map of the environment as the user moves around, allowing the device to re-localize itself within a known space.

	== Advantages ==		== Advantages ==
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	* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (e.g., blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.		* '''Environmental Dependence:''' Tracking performance can degrade in environments with poor lighting, few visual features (e.g., blank walls), or highly repetitive textures. Reflective surfaces can also sometimes cause issues.
	* '''Computational Load:''' Processing sensor data and running tracking algorithms (especially SLAM/VIO) requires significant processing power on the device itself (HMD or connected computer), potentially impacting battery life or requiring more powerful onboard processors.		* '''Computational Load:''' Processing sensor data and running tracking algorithms (especially SLAM/VIO) requires significant processing power on the device itself (HMD or connected computer), potentially impacting battery life or requiring more powerful onboard processors.
	* '''Drift:''' While modern systems are robust, markerless tracking can sometimes accumulate small positional errors over time (drift), potentially requiring occasional recalibration or re-localization, although [[environment mapping]] helps significantly.		* '''Drift:''' While modern systems are robust, markerless tracking can sometimes accumulate small positional errors over time (drift), potentially requiring occasional recalibration or re-localization, although environment mapping helps significantly.
	* '''Initialization:''' The system needs to initialize and potentially map a new area before tracking becomes fully stable.		* '''Initialization:''' The system needs to initialize and potentially map a new area before tracking becomes fully stable.

	== Examples of Devices/Platforms Using Inside-out Tracking ==		== Examples of Devices and Platforms Using Inside-out Tracking ==
	Many modern VR/AR/MR systems utilize markerless inside-out tracking:		Many modern VR/AR/MR systems utilize markerless inside-out tracking:
	* '''[[Meta Quest]] series''' ([[Oculus Quest]], Quest 2, Quest 3, Quest Pro) - Uses the "[[Oculus Insight]]" tracking system.		* '''[[Meta Quest]] series''' ([[Oculus Quest]], Quest 2, Quest 3, [[Meta Quest 3S\|Quest 3S]], [[Meta Quest Pro\|Quest Pro]]) - Uses the "[[Oculus Insight]]" tracking system.
	* '''[[Oculus Rift S]]''' - Also used Oculus Insight.		* '''[[Oculus Rift S]]''' - Also used Oculus Insight.
	* '''[[Windows Mixed Reality]]''' platform headsets (e.g., [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).		* '''[[Windows Mixed Reality]]''' platform headsets (e.g., [[HP Reverb]] G1 & G2, [[Samsung HMD Odyssey]], Acer AH101, Lenovo Explorer).
	* '''[[HTC Vive Cosmos]]''' (with standard faceplate), '''[[HTC Vive Focus]]''' series, '''[[HTC Vive XR Elite]]'''.		* '''[[HTC Vive Cosmos]]''' (with standard faceplate), '''[[HTC Vive Focus]]''' series, '''[[HTC Vive XR Elite]]'''.
	* '''Pico Neo''' series (e.g., Pico Neo 3, Pico 4).		* '''Pico Neo''' series (e.g., Pico Neo 3, Pico 4).
	* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets).		* '''[[Microsoft HoloLens]]''' 1 and 2 (AR headsets using [[HPU (Holographic Processing Unit)\|HPUs]] for processing).
	* '''[[Valve Index]]''' (Uses inside-out cameras primarily for passthrough view, room setup scanning, and potentially some experimental features, but relies on [[Lighthouse]] (outside-in) for its primary HMD and controller tracking).		* '''[[Valve Index]]''' (Uses inside-out cameras primarily for passthrough view, room setup scanning, and potentially some experimental features, but relies on [[Lighthouse]] (outside-in) for its primary HMD and controller tracking).
	* '''[[PlayStation VR2]]''' (Uses inside-out cameras for HMD and controller tracking).		* '''[[PlayStation VR2]]''' (Uses inside-out cameras for HMD and controller tracking).
	* '''[[Apple Vision Pro]]''' (MR headset).		* '''[[Apple Vision Pro]]''' (MR headset).
			* '''[[Lenovo Mirage Solo]]''' (Used Google's [[WorldSense]] tracking).
			* '''[[Magic Leap]]''' 1 and 2.
	* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing/orientation).		* '''[[Nintendo Wii Remote]]''' (non-VR example using marker-based inside-out tracking for pointing/orientation).

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	<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>		<ref name="m249">{{cite web \| title=Inside-out tracking \| website=XVRWiki \| date=2024-09-30 \| url=https://www.xvrwiki.org/wiki/Inside-out_tracking \| access-date=2024-10-05}}</ref>
	<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>		<ref name=”Boger2014Overview”> Boger, Y. (2014). Overview of positional tracking technologies for virtual reality. Retrieved from http://www.roadtovr.com/overview-of-positional-tracking-technologies-virtual-reality/</ref>
	<ref name=”Langley2017”> Langley, H. (2017). Inside-out v Outside-in: How VR tracking works, and how it's going to change. Retrieved from https://www.wareable.com/vr/inside-out-vs-outside-in-vr-tracking-343</ref> {{comment\|Note: ~~Kept this ref from original page, seems relevant for~~ advantages/disadvantages context}}		<ref name=”Langley2017”> Langley, H. (2017). Inside-out v Outside-in: How VR tracking works, and how it's going to change. Retrieved from https://www.wareable.com/vr/inside-out-vs-outside-in-vr-tracking-343</ref> {{comment\|Note: Supports advantages/disadvantages context}}
	<ref name=”ARVRTips2020”> AR/VR Tips (2020). VR Headset Comparison. Retrieved from https://arvrtips.com/vr-headset-comparison-tool/</ref> {{comment\|Note: ~~Kept this ref from original page, potentially~~ supports device examples}}		<ref name=”ARVRTips2020”> AR/VR Tips (2020). VR Headset Comparison. Retrieved from https://arvrtips.com/vr-headset-comparison-tool/</ref> {{comment\|Note: Potentially supports device examples}}
	</references>		</references>