Inside-out tracking: Difference between revisions
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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). | * '''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=”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]] | ||