Abstract: Systems and techniques are described herein for pose estimation of a person. For instance, a method for pose estimation of a person is provided. The method may include obtaining an image of the person; obtaining a head pose of the person; determining a search region of the image based on the head pose; and determining a pose of the person based on the search region.

Abstract: Techniques and systems are provided for performing data transfers. For instance, a process can include receiving an indication to perform a data transfer; determining, based on a feature map of an environment, a location of an extended reality (XR) device in the environment; determining a first pose of the XR device; obtaining, from the feature map, location information for a target device in the environment; identifying the target device based on the location and the first pose of the XR device; transmitting, to the target device in response to the indication to perform the data transfer, a request to initiate the data transfer; receiving a second pose of the target device; and performing the data transfer based on the received second pose and the first pose of the XR device.

Abstract: Systems and methods for computationally efficient and precise transformation recovery using two image frames are provided. A key image frame and a tracked image frame are selected from a series of image frames, a plurality of points on the key image frame are selected, and the plurality of points are then projected onto the tracked image frame to produce a number of corresponding points. Then, for each corresponding point, a patch of pixels is defined centered on the corresponding point. Each pixel of the patch is reprojected back onto the key image frame to identify a reprojected pixel in that image frame. An intensity value for each reprojected pixel is determined and each patch is parameterized. A normal equation for each patch is determined and then solved for the transformation.