Abstract: The described implementations relate to images and depth information and generating useful information from the images and depth information. One example can identify planes in a semantically-labeled 3D voxel representation of a scene. The example can infer missing information by extending planes associated with structural elements of the scene. The example can also generate a watertight manifold representation of the scene at least in part from the inferred missing information.

Abstract: The described implementations relate to images and depth information and generating useful information from the images and depth information. One example can identify planes in a semantically-labeled 3D voxel representation of a scene. The example can infer missing information by extending planes associated with structural elements of the scene. The example can also generate a watertight manifold representation of the scene at least in part from the inferred missing information.

Abstract: Examples are disclosed that relate to tracking a pose of a handheld object used with a head-mounted display device. In one example, a method comprises: receiving image data from an image sensing system; detecting a plurality of feature points of the handheld object in a frame of the image data; receiving inertial measurement unit (IMU) data from an IMU of the handheld object; based on detecting the plurality of feature points and receiving the IMU data, determining a first pose of the handheld object; determining that at least a portion of the plurality of feature points is not detected in another frame of the image data; using the IMU data, updating the first pose of the handheld object to a second pose; and body-locking the second pose of the handheld object to a body location on a user wearing the head-mounted display device.

Abstract: Examples are disclosed that relate to tracking a pose of a handheld object used with a head-mounted display device. In one example, a method comprises: receiving image data from an image sensing system; detecting a plurality of feature points of the handheld object in a frame of the image data; receiving inertial measurement unit (IMU) data from an IMU of the handheld object; based on detecting the plurality of feature points and receiving the IMU data, determining a first pose of the handheld object; determining that at least a portion of the plurality of feature points is not detected in another frame of the image data; using the IMU data, updating the first pose of the handheld object to a second pose; and body-locking the second pose of the handheld object to a body location on a user wearing the head-mounted display device.

Abstract: A facility for generating at least one image is described. For each of multiple registered photography scenarios, the facility determines a suitable score for the scenario based upon state of a photography device. The facility selects a scenario having a suitability score that is no lower than any other determined suitability score. The facility then captures a sequence of one or more frames in a manner specified for the selected scenario, and processes that captured sequence of frames in a manner specified for the selected scenario to obtain at least one image.