Abstract: Implementations of the disclosed technology include techniques for autonomously collecting image data, and generating photo summaries based thereon. In some implementations, a plurality of images may be autonomously sampled from an available stream of image data. For example, a camera application of a smartphone or other mobile computing device may present a live preview based on a stream of data from an image capture device. The live stream of image capture data may be sampled and the most interesting photos preserved for further filtering and presentation. The preserved photos may be further winnowed as a photo session continues and an image object generated summarizing the remaining photos. Accordingly, image capture data may be autonomously collected, filtered, and formatted to enable a photographer to see what moments they missed manually capturing during a photo session.

Abstract: Techniques for determining motion saliency in video content using center-surround receptive fields. In some implementations, images or frames from a video may be apportioned into non-overlapped regions, for example, by applying a rectilinear grid. For each grid region, or cell, motion consistency may be measured between the center and surround area of that cell across frames of the video. Consistent motion across the center-surround area may indicate that the corresponding region has low variation. The larger the difference between center-surround motions in a cell, the more likely the region has high motion saliency.

Abstract: Techniques for determining motion saliency in video content using center-surround receptive fields. In some implementations, images or frames from a video may be apportioned into non-overlapped regions, for example, by applying a rectilinear grid. For each grid region, or cell, motion consistency may be measured between the center and surround area of that cell across frames of the video. Consistent motion across the center-surround area may indicate that the corresponding region has low variation. The larger the difference between center-surround motions in a cell, the more likely the region has high motion saliency.

Abstract: The disclosed technology includes techniques for improved content coverage in automatically-generated content summaries. The technique may include clustering a set of input content, determining diffusion for each cluster, and selecting representatives of each cluster to optimize other secondary metrics. Various types of input content may be used, including groups of images, video clips, or other multimedia content. Contiguous content may be manually or programmatically divided into discrete portions before clustering, for example, a lengthy video divided into a number of short clips. In some implementations, the disclosed technique may be implemented effectively on a mobile device. In other words, the processing required may be computationally feasible for execution on a smartphone or similar device.

Abstract: Disclosed are methods for automatically generating commands to transform a video sequence based on information regarding speaking participants derived from the audio and video signals. The audio stream is analyzed to detect individual speakers and the video is optionally analyzed to detect lip movement to determine a probability that a detected participant is speaking. Commands are then generated to transform the video stream consistent with the identified speaker.