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Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity Recognition

Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity Recognition

This video was recorded at 12th European Conference on Computer Vision (ECCV), Firenze 2012. This paper addresses a new problem, that of multiscale activity recognition. Our goal is to detect and localize a wide range of activities, including individual actions and group activities, which may simultaneously co-occur in high-resolution video. The video resolution allows for digital zoom-in (or zoom-out) for examining fine details (or coarser scales), as needed for recognition. The key challenge is how to avoid running a multitude of detectors at all spatiotemporal scales, and yet arrive at a holistically consistent video interpretation. To this end, we use a three-layered AND-OR graph to jointly model group activities, individual actions, and participating objects. The AND-OR graph allows a... Show More
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