Abstract: In one implementation, a method includes receiving a warped image representing simulated reality (SR) content (e.g., to be displayed in a display space), the warped image having a plurality of pixels at respective locations uniformly spaced in a grid pattern in a warped space, wherein the plurality of pixels are respectively associated with a plurality of respective pixel values and a plurality of respective scaling factors indicating a plurality of respective resolutions at a plurality of respective locations of the SR content (e.g., in the display space). The method includes processing the warped image in the warped space based on the plurality of respective scaling factors to generate a processed warped image and transmitting the processed warped image.

Abstract: A method includes obtaining first pass-through image data characterized by a first pose. The method includes obtaining respective pixel characterization vectors for pixels in the first pass-through image data. The method includes identifying a feature of an object within the first pass-through image data in accordance with a determination that pixel characterization vectors for the feature satisfy a feature confidence threshold. The method includes displaying the first pass-through image data and an AR display marker that corresponds to the feature. The method includes obtaining second pass-through image data characterized by a second pose. The method includes transforming the AR display marker to a position associated with the second pose in order to track the feature. The method includes displaying the second pass-through image data and maintaining display of the AR display marker that corresponds to the feature of the object based on the transformation.

Abstract: In one implementation, a method of generating a bit stream encoding a video stream is performed by a device including one or more processors and non-transitory memory. The method includes decomposing a video stream into a plurality of frequency band video streams. The method includes determining a target bitrate and determining, for each frequency band video stream, a respective frequency band bit rate based on the target bit rate. The method includes encoding each of the plurality of frequency band video streams at its respective frequency band bit rate and transmitting, over a channel, each encoded frequency band video stream.

Abstract: In one implementation, a method includes receiving a warped image representing simulated reality (SR) content (e.g., to be displayed in a display space), the warped image having a plurality of pixels at respective locations uniformly spaced in a grid pattern in a warped space, wherein the plurality of pixels are respectively associated with a plurality of respective pixel values and a plurality of respective scaling factors indicating a plurality of respective resolutions at a plurality of respective locations of the SR content (e.g., in the display space). The method includes processing the warped image in the warped space based on the plurality of respective scaling factors to generate a processed warped image and transmitting the processed warped image.

Abstract: A method includes obtaining first pass-through image data characterized by a first pose. The method includes obtaining respective pixel characterization vectors for pixels in the first pass-through image data. The method includes identifying a feature of an object within the first pass-through image data in accordance with a determination that pixel characterization vectors for the feature satisfy a feature confidence threshold. The method includes displaying the first pass-through image data and an AR display marker that corresponds to the feature. The method includes obtaining second pass-through image data characterized by a second pose. The method includes transforming the AR display marker to a position associated with the second pose in order to track the feature. The method includes displaying the second pass-through image data and maintaining display of the AR display marker that corresponds to the feature of the object based on the transformation.

Abstract: Various implementations provide 3D representations of objects. Such representations may be based on 3D point cloud and/or 2D image inputs that are obtained based on sensor data, e.g., images, depth data, motion data, etc. 3D point cloud input may be used for part segmentation and/or to determine position and/or orientation of object parts, e.g., generating 3D bounding boxes representing the sizes, positions, and orientations, of object parts. 2D image input may be used for part attribute recognition, e.g., to determine whether a chair legs part has a particular type such as star-shaped, straight down, crossed-shaped, etc. Part attributes may be used to produce a relatively simple and relatively accurate representation of the shape of each part within a respective area, e.g., within a bounding box determined for each part using the 3D point cloud input.

Abstract: In one implementation, a method includes receiving a warped image representing simulated reality (SR) content (e.g., to be displayed in a display space), the warped image having a plurality of pixels at respective locations uniformly spaced in a grid pattern in a warped space, wherein the plurality of pixels are respectively associated with a plurality of respective pixel values and a plurality of respective scaling factors indicating a plurality of respective resolutions at a plurality of respective locations of the SR content (e.g., in the display space). The method includes processing the warped image in the warped space based on the plurality of respective scaling factors to generate a processed warped image and transmitting the processed warped image.

Abstract: A method includes obtaining first pass-through image data characterized by a first pose. The method includes obtaining respective pixel characterization vectors for pixels in the first pass-through image data. The method includes identifying a feature of an object within the first pass-through image data in accordance with a determination that pixel characterization vectors for the feature satisfy a feature confidence threshold. The method includes displaying the first pass-through image data and an AR display marker that corresponds to the feature. The method includes obtaining second pass-through image data characterized by a second pose. The method includes transforming the AR display marker to a position associated with the second pose in order to track the feature. The method includes displaying the second pass-through image data and maintaining display of the AR display marker that corresponds to the feature of the object based on the transformation.