Abstract: Systems, methods, and computer readable media to rapidly identify and track an arbitrary sized object through a temporal sequence of frames is described. The object being tracked may initially be identified via a specified or otherwise known region-of-interest (ROI). A portion of that ROI can be used to generate an initial or reference histogram and luminosity measure, metrics that may be used to identify the ROI in a subsequent frame. For a frame subsequent to the initial or reference frame, a series of putative ROIs (each having its own location and size) may be identified and the “best” of the identified ROIs selected. As used here, the term “best” simply means that the more similar two frames' histograms and luminosity measures are, the better one is with respect to the other.

Abstract: Techniques to detect subject and camera motion in a set of consecutively captured image frames are disclosed. More particularly, techniques disclosed herein temporally track two sets of downscaled images to detect motion. One set may contain higher resolution and the other set lower resolution of the same images. For each set, a coefficient of variation may be computed across the set of images for each sample in the downscaled image to detect motion and generate a change mask. The information in the change mask can be used for various applications, including determining how to capture a next image in the sequence.

Abstract: Systems, methods, and computer readable media to rapidly identify and track an arbitrary sized object through a temporal sequence of frames is described. The object being tracked may initially be identified via a specified or otherwise known region-of-interest (ROI). A portion of that ROI can be used to generate an initial or reference histogram and luminosity measure, metrics that may be used to identify the ROI in a subsequent frame. For a frame subsequent to the initial or reference frame, a series of putative ROIs (each having its own location and size) may be identified and the “best” of the identified ROIs selected. As used here, the term “best” simply means that the more similar two frames' histograms and luminosity measures are, the better one is with respect to the other.

Abstract: Techniques to detect subject and camera motion in a set of consecutively captured image frames are disclosed. More particularly, techniques disclosed herein temporally track two sets of downscaled images to detect motion. One set may contain higher resolution and the other set lower resolution of the same images. For each set, a coefficient of variation may be computed across the set of images for each sample in the downscaled image to detect motion and generate a change mask. The information in the change mask can be used for various applications, including determining how to capture a next image in the sequence.