Leveraging Limited Autonomous Mobility to Frame Attractive Group Photos

Robot photographers have appeared in a variety of novelty settings over the past few years and typically have exploited rudimentary image-content-based approaches to identifying potential photographic subjects. These approaches are primarily limited to human subjects and further progress along content-based lines is hamstrung by slow progress on the general computer vision problem. In this paper, we present a mobile robot system which solves the group-picture-framing problem without requiring content-based methods. The system finds photographic subjects based on measurements of motion parallax obtained via optical flow during robot movements. Our method requires only sufficient contrast to permit reasonably accurate sparse optical flow field estimation and is completely independent of any content-based image heuristics. The result is a working mobile robot system that can correctly photograph human and non-human subjects in a variety of posed-subject situations, and produce well-framed, cropped images for printing on standard-sized photo paper.

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