Amazon Technologies, Inc.

Samuel Nathan Hallman

Tian Lan

Jue Wang

Gerard Guy Medioni

Jayakrishnan Kumar Eledath

Petko Tsonev

Hui Liang

Kostia Robert

Michael Francis O'Malley

An imaging device may capture images of a scene, where the scene includes retroreflective materials. Where visual images and depth images are captured from a scene, and the depth images have ratios of supersaturated pixels that are less than a predetermined threshold, a location map of the scene is generated or updated based on the depth images. Where the ratios are greater than the predetermined threshold, the location map of the scene is generated or updated based on the visual images. Additionally, where each of a plurality of imaging devices detect concentrations of supersaturated pixels beyond a predetermined threshold or limit within their respective fields of view, an actor present on the scene may be determined to be wearing retroreflective material, or otherwise designated as a source of the supersaturation, and tracked with the scene based on coverage areas that are determined to have excessive ratios of supersaturated pixels.

Detecting and locating actors in scenes based on degraded or supersaturated depth data

Motion of actors within a scene may be detected based on imaging data, using machine learning tools operating on cameras that captured the imaging data. The machine learning tools process images to perform a number of tasks, including detecting heads of actors, and sets of pixels corresponding to the actors, before constructing line segments from the heads of the actors to floor surfaces on which the actors stand or walk. The line segments are aligned along lines extending from locations of heads within an image to a vanishing point of a camera that captured the image. Trajectories of actors and visual data are transferred from the cameras to a central server, which links trajectories captured by multiple cameras and locates detected actors throughout the scene, even when the actors are not detected within a field of view of at least one camera.

Locally and globally locating actors by digital cameras and machine learning

Growing community of inventors

Seattle, WA, United States of America

Samuel Nathan Hallman