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Pose tracking
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Pose tracking
In 3D human-computer interaction, positional tracking, also called pose tracking, is a process that tracks the position and/or orientation of head-mounted displays, controllers, or other input devices within Euclidean space. Pose tracking is often referred to as 6DOF tracking, for the six degrees of freedom in which the objects are often tracked.
In some consumer GPS systems, orientation data is added additionally using magnetometers, which give partial orientation information, but not the full orientation that pose tracking provides.
In VR, it is paramount that pose tracking is both accurate and precise so as not to break the illusion of a being in virtual world. Several methods of tracking the position and orientation (pitch, yaw and roll) of a display and any associated objects or devices have been developed to achieve this. Many methods utilize sensors which repeatedly record signals from transmitters on or near the tracked object(s), and then send that data to the computer in order to maintain an approximation of their physical locations. A popular tracking method is Lighthouse tracking. By and large, these physical locations are identified and defined using one or more of three coordinate systems: the Cartesian rectilinear system, the spherical polar system, and the cylindrical system. Many interfaces have also been designed to monitor and control one's movement within and interaction with the virtual 3D space; such interfaces must work closely with positional tracking systems to provide a seamless user experience.
Another type of pose tracking used more often in newer systems is referred to as inside-out tracking, including simultaneous localization and mapping (SLAM) or visual-inertial odometry (VIO). An example of a device that uses inside-out positional tracking is the Oculus Quest 2.
Wireless tracking uses a set of anchors that are placed around the perimeter of the tracking space and one or more tags that are tracked. This system is similar in concept to GPS, but works both indoors and outdoors. Sometimes referred to as indoor GPS. The tags triangulate their 3D position using the anchors placed around the perimeter. A wireless technology called Ultra Wideband has enabled the position tracking to reach a precision of under 100 mm. By using sensor fusion and high speed algorithms, the tracking precision can reach 5 mm level with update speeds of 200 Hz or 5 ms latency.
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Optical tracking uses cameras placed on or around the headset to determine position and orientation based on computer vision algorithms. This method is based on the same principle as stereoscopic human vision. When a person looks at an object using binocular vision, they are able to define approximately at what distance the object is placed due to the difference in perspective between the two eyes. In optical tracking, cameras are calibrated to determine the distance to the object and its position in space. Optical systems are reliable and relatively inexpensive, but they can be difficult to calibrate. Furthermore, the system requires a direct line of light without occlusions, otherwise it will receive wrong data.
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Pose tracking AI simulator
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Pose tracking
In 3D human-computer interaction, positional tracking, also called pose tracking, is a process that tracks the position and/or orientation of head-mounted displays, controllers, or other input devices within Euclidean space. Pose tracking is often referred to as 6DOF tracking, for the six degrees of freedom in which the objects are often tracked.
In some consumer GPS systems, orientation data is added additionally using magnetometers, which give partial orientation information, but not the full orientation that pose tracking provides.
In VR, it is paramount that pose tracking is both accurate and precise so as not to break the illusion of a being in virtual world. Several methods of tracking the position and orientation (pitch, yaw and roll) of a display and any associated objects or devices have been developed to achieve this. Many methods utilize sensors which repeatedly record signals from transmitters on or near the tracked object(s), and then send that data to the computer in order to maintain an approximation of their physical locations. A popular tracking method is Lighthouse tracking. By and large, these physical locations are identified and defined using one or more of three coordinate systems: the Cartesian rectilinear system, the spherical polar system, and the cylindrical system. Many interfaces have also been designed to monitor and control one's movement within and interaction with the virtual 3D space; such interfaces must work closely with positional tracking systems to provide a seamless user experience.
Another type of pose tracking used more often in newer systems is referred to as inside-out tracking, including simultaneous localization and mapping (SLAM) or visual-inertial odometry (VIO). An example of a device that uses inside-out positional tracking is the Oculus Quest 2.
Wireless tracking uses a set of anchors that are placed around the perimeter of the tracking space and one or more tags that are tracked. This system is similar in concept to GPS, but works both indoors and outdoors. Sometimes referred to as indoor GPS. The tags triangulate their 3D position using the anchors placed around the perimeter. A wireless technology called Ultra Wideband has enabled the position tracking to reach a precision of under 100 mm. By using sensor fusion and high speed algorithms, the tracking precision can reach 5 mm level with update speeds of 200 Hz or 5 ms latency.
Pros:
Cons:
Optical tracking uses cameras placed on or around the headset to determine position and orientation based on computer vision algorithms. This method is based on the same principle as stereoscopic human vision. When a person looks at an object using binocular vision, they are able to define approximately at what distance the object is placed due to the difference in perspective between the two eyes. In optical tracking, cameras are calibrated to determine the distance to the object and its position in space. Optical systems are reliable and relatively inexpensive, but they can be difficult to calibrate. Furthermore, the system requires a direct line of light without occlusions, otherwise it will receive wrong data.
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