Abstract: The invention provides, in some aspects, a method of access control that includes receiving one or more frames (“depth frames”) of a depth image stream acquired by a depth camera and, for each of those depth frames, generating one or more scores of the liveness of the image and/or of a candidate individual therein. The method includes creating a point cloud from a respective depth frame and generating the liveness score from a vector based on geometric characteristics of eigenvalues of point-wise neighborhoods within that point cloud. That vector, which characterizes the respective depth frame and surface contours of a face of the candidate individual represented therein, can serve as a measure of how that surface varies and, thereby, permits it to be distinguished from a spoof, e.g., a depth image of faces printed on paper or shown a digital display.

Abstract: Aspects of the invention provide a method of face recognition that includes receiving plural frames of a video stream imaging a candidate individual, e.g., in the field of view of a camera, and generating for each of those frames a score of the image and/or of the candidate therein. This can include a score (or count) indicative of the number of individuals present in the frame, a pose of the candidate individual (e.g., face-on or otherwise), blur in the image, and so forth. The method further includes selecting, based on the respective scores of the frames, a subset of the frames for matching by a face recognizer against a set of one or more images of designated individuals. That set may be of individuals approved for access, individuals to be prevented for access, or otherwise. An output can be generated based on such matching by the face recognizer.

Abstract: Aspects of the invention provide, in some aspects, a method of face recognition that includes receiving plural frames of a video stream imaging a candidate individual, e.g., in the field of view of a camera, and generating for each of those frames a score of the image and/or of the candidate therein. This can include, for example, a score (or count) indicative of the number of individuals present in the frame, a pose of the candidate individual (e.g., face-on or otherwise), blur in the image, and so forth. The method further includes selecting, based on the respective scores of the frames, a subset of the frames for matching by a face recognizer against a set of one or more images of designated individuals. That set may be of individuals approved for access, individuals to be prevented for access, or otherwise. An output is generated, according to the method, based on such matching by the face recognizer.

Abstract: Aspects of the invention provide a vision pipeline-based method of censusing a crowd that includes presenting content on an outdoor digital display or other content player (e.g., a loudspeaker) and capturing with a video camera or other image acquisition device frames or other time-wise succession of images of a scene in the field of view or otherwise in the vicinity of the display/player. First and second people detectors (both, for example, face detectors) are used to determine respective counts of persons in the scene. Estimated viewing statistics, generated with a detection pipeline that includes the first people detector and a tracker, include at least one of (i) a number of persons in the scene that viewed the content on the player, and (ii) for at least one of those persons, a duration during which he/she was in the scene and/or looking toward the player.