Abstract: A computer-implemented method, comprising accessing an image comprising a handheld device, wherein the image is captured by one or more cameras associated with the computing device, generating a cropped image that comprises a hand of a user or the handheld device from the image by processing the image, generating a vision-based six degrees of freedom (6DoF) pose estimation for the handheld device by processing the cropped image, metadata associated with the image, and first sensor data from one or more sensors associated with the handheld device, generating a map-based 6DoF pose estimation using the handheld device, and generating a final 6DoF pose estimation for the handheld device based on the vision-based 6DoF pose estimation and the map-based 6DoF pose estimation generated using the handheld device.

Abstract: In one embodiment, a method includes accessing an image comprising a handheld device, the image being captured by one or more cameras associated with the computing device, generating a cropped image that comprises a hand of a user or the handheld device from the image by processing the image using a first machine-learning model, generating a vision-based 6DoF pose estimation for the handheld device by processing the cropped image, metadata associated with the image, and first sensor data from one or more sensors associated with the handheld device using a second machine-learning model, generating a motion-sensor-based 6DoF pose estimation for the handheld device by integrating second sensor data from the one or more sensors associated with the handheld device, and generating a final 6DoF pose estimation for the handheld device based on the vision-based 6DoF pose estimation and the motion-sensor-based 6DoF pose estimation.

Abstract: In one embodiment, a method for tracking includes receiving motion data captured by a motion sensor of a wearable device, generating a pose of the wearable device based on the motion data, capturing a first frame of the wearable device by a camera using a first exposure time, identifying, in the first frame, a pattern of lights disposed on the wearable device, capturing a second frame of the wearable device by the camera using a second exposure time, identifying, in the second frame, predetermined features of the wearable device, and adjusting the pose of the wearable device in the environment based on the identified pattern of light in the first frame or the identified predetermined features in the second frame. The method utilizes the predetermined features for tracking the wearable device in a visible-light frame under specific light conditions to improve the accuracy of the pose of controller.

Abstract: A head-mounted display (HMD) is configured to capture images and/or video of a local area. The HMD includes an imaging assembly and a controller. The imaging assembly includes a plurality of cameras positioned at different locations on the HMD and oriented to capture images of different portions of a local area surrounding the HMD. The controller generates imaging instructions for each camera using image information. The imaging instructions cause respective midpoints of exposure times for each camera to occur at a same time value for each of the captured images. The cameras capture images of the local area in accordance with the imaging instructions. The controller determines a location of the HMD in the local area using the captured images and updates a model that represents a mapping function of the depth and exposure settings of the local area.

Abstract: A virtual reality (VR) system tracks the location and position of a controller using image sensors on a headset and a controller. The headset and controller provide a first and second view of a user's environment. Using its camera, the headset generates a map of the environment and identifies its location within it. Based headset's location, the VR system generates a simulated world of the environment and displays it to the user. The headset also estimates the location of the controller. Based on the estimated location, the headset sends a portion of the map to the controller. The controller determines its pose using the portion of the map, the image sensors, and additional sensors. The controller sends its pose and an updated portion of the map to the headset. Based on the controller's pose and updated portion of the map, the VR system modifies the content displayed to the user.

Abstract: An artificial reality system is described that implements adaptive degrees-of-freedom (DOF) selection when tracking frames of reference and rendering artificial reality content. In one example, the artificial reality system comprises a head mounted display (HMD) that outputs rendered artificial reality content. A performance monitor determines one or more performance indicators associated with the artificial reality system. A degree-of-freedom (DOF) selector applies one or more policies to the performance indicators to select between a first mode in which a pose tracker computes one or more poses of the HMD within the 3D environment using 6DOF and a second mode in which the pose tracker computes the one or more poses using 3DOF. The pose tracker computes the one or more poses for the HMD within the 3D environment in accordance with the selected mode. A rendering engine renders the content for the artificial reality application based on the computed pose.

Abstract: An artificial reality system is described that implements adaptive degrees-of-freedom (DOF) selection when tracking frames of reference and rendering artificial reality content. In one example, the artificial reality system comprises a head mounted display (HMD) that outputs rendered artificial reality content. A performance monitor determines one or more performance indicators associated with the artificial reality system. A degree-of-freedom (DOF) selector applies one or more policies to the performance indicators to select between a first mode in which a pose tracker computes one or more poses of the HMD within the 3D environment using 6DOF and a second mode in which the pose tracker computes the one or more poses using 3DOF. The pose tracker computes the one or more poses for the HMD within the 3D environment in accordance with the selected mode. A rendering engine renders the content for the artificial reality application based on the computed pose.

Abstract: A hand-held controller is enables a user to manipulate objects in a VR environment with hand movement. The hand-held controller includes a handle, a ring attached to an end of the handle and one or more light emitting diodes (LEDs). The handle has appropriate shape and dimensions so that it can be grasped by the user's hand. The ring has an outer body that includes an inner surface that is formed with one or more concave dome and an outer surface facing away from the inner surface. Each of the one or more LED is mounted under a concaved dome. Light emitted from the LED spreads at the concaved dome to form uniform illuminous intensity. The light transmits out of the body through the outer surface of the outer body. The light can be captured by a camera for tracking the hand-held controller.

Abstract: A head-mounted display (HMD) is configured to capture images and/or video of a local area. The HMD includes an imaging assembly and a controller. The imaging assembly includes a plurality of cameras positioned at different locations on the HMD and oriented to capture images of different portions of a local area surrounding the HMD. The controller generates imaging instructions for each camera using image information. The imaging instructions cause respective midpoints of exposure times for each camera to occur at a same time value for each of the captured images. The cameras capture images of the local area in accordance with the imaging instructions. The controller determines a location of the HMD in the local area using the captured images and updates a model that represents a mapping function of the depth and exposure settings of the local area.

Abstract: A head-mounted display (HMD) is configured to capture images and/or video of a local area. The HMD includes an imaging assembly and a controller. The imaging assembly includes a plurality of cameras positioned at different locations on the HMD and oriented to capture images of different portions of a local area surrounding the HMD. The controller generates imaging instructions for each camera using image information. The imaging instructions cause respective midpoints of exposure times for each camera to occur at a same time value for each of the captured images. The cameras capture images of the local area in accordance with the imaging instructions. The controller determines a location of the HMD in the local area using the captured images and updates a model that represents a mapping function of the depth and exposure settings of the local area.

Abstract: A calibration system is configured to determine calibration information of a head-mounted display (HMD). The calibration system comprises a first, second, and third planar grid, a movable platform, and a calibration controller. Each planar grid includes a plurality of fiducial markers that are displayed in accordance with a display pattern. The HMD is coupled to the movable platform, which moves the HMD before the planar grids as a plurality of cameras on the HMD captures images of the planar grids with fiducial markers. The calibration controller controls a motion sequence of the movable platform and determines calibration information for each of the cameras on the HMD and calibration information for an inertial measurement unit (IMU) within the HMD. The calibration information is based in part on a parameterized model of the motion sequence of the HMD.

Abstract: A hand-held controller is enables a user to manipulate objects in a VR environment with hand movement. The hand-held controller includes a handle, a ring attached to an end of the handle and one or more light emitting diodes (LEDs). The handle has appropriate shape and dimensions so that it can be grasped by the user's hand. The ring has an outer body that includes an inner surface that is formed with one or more concave dome and an outer surface facing away from the inner surface. Each of the one or more LED is mounted under a concaved dome. Light emitted from the LED spreads at the concaved dome to form uniform illuminous intensity. The light transmits out of the body through the outer surface of the outer body. The light can be captured by a camera for tracking the hand-held controller.

Abstract: A virtual reality (VR) headset calibration system calibrates a VR headset, which includes a plurality of locators and an inertial measurement unit (IMU) generating output signals indicative of motion of the VR headset. The system comprises a calibration controller configured to receive a headset model of the VR headset that identifies expected positions of each of the locators. The controller controls cameras to capture images of the VR headset while the headset is moved along a predetermined path. The images detect actual positions of the locators during the movement along the predetermined path. Calibration parameters for the locators are generated based on differences between the actual positions and the expected positions. Calibration parameters for the IMU are generated based on the calibration parameters for the locators and differences between expected and actual signals output by the IMU. The calibration parameters are stored to the VR headset.

Abstract: A head-mounted display (HMD) is configured to capture images and/or video of a local area. The HMD includes an imaging assembly and a controller. The imaging assembly includes a plurality of cameras positioned at different locations on the HMD and oriented to capture images of different portions of a local area surrounding the HMD. The controller generates imaging instructions for each camera using image information. The imaging instructions cause respective midpoints of exposure times for each camera to occur at a same time value for each of the captured images. The cameras capture images of the local area in accordance with the imaging instructions. The controller determines a location of the HMD in the local area using the captured images and updates a model that represents a mapping function of the depth and exposure settings of the local area.

Abstract: A calibration system is configured to determine calibration information of a head-mounted display (HMD). The calibration system comprises a first, second, and third planar grid, a movable platform, and a calibration controller. Each planar grid includes a plurality of fiducial markers that are displayed in accordance with a display pattern. The HMD is coupled to the movable platform, which moves the HMD before the planar grids as a plurality of cameras on the HMD captures images of the planar grids with fiducial markers. The calibration controller controls a motion sequence of the movable platform and determines calibration information for each of the cameras on the HMD and calibration information for an inertial measurement unit (IMU) within the HMD. The calibration information is based in part on a parameterized model of the motion sequence of the HMD.

Abstract: A virtual reality (VR) headset calibration system calibrates a VR headset, which includes a plurality of locators and an inertial measurement unit (IMU) generating output signals indicative of motion of the VR headset. The system comprises a calibration controller configured to receive a headset model of the VR headset that identifies expected positions of each of the locators. The controller controls cameras to capture images of the VR headset while the headset is moved along a predetermined path. The images detect actual positions of the locators during the movement along the predetermined path. Calibration parameters for the locators are generated based on differences between the actual positions and the expected positions. Calibration parameters for the IMU are generated based on the calibration parameters for the locators and differences between expected and actual signals output by the IMU. The calibration parameters are stored to the VR headset.

Abstract: A virtual reality (VR) headset calibration system calibrates a VR headset, which includes a plurality of locators and an inertial measurement unit (IMU) generating output signals indicative of motion of the VR headset. The system comprises a calibration controller configured to receive a headset model of the VR headset that identifies expected positions of each of the locators. The controller controls cameras to capture images of the VR headset while the headset is moved along a predetermined path. The images detect actual positions of the locators during the movement along the predetermined path. Calibration parameters for the locators are generated based on differences between the actual positions and the expected positions. Calibration parameters for the IMU are generated based on the calibration parameters for the locators and differences between expected and actual signals output by the IMU. The calibration parameters are stored to the VR headset.