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Action localization and classification in long-distance surveillance
Author(s): Eli Chen; Oren Haik; Yitzhak Yitzhaky
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Paper Abstract

Suspicious human behaviors can be defined by the user, and in long distance imaging it may include bending the body during walking or crawling, in contrast to regular walking for instance. State-of-the-art methods using convolutional neural networks (CNNs) dealt in general with “clean” signals, in which the object of interest is relatively close to the camera, and therefore fairly clear and easily distinguished from the surrounding environment. This makes it easier to capture detailed information regarding the object and its action. However, in relatively long distance imaging (few kilometers and above) additional difficulties occur which affect the performances of these tasks, since the captured videos are likely to be degraded by the atmospheric path that cause blur and spatiotemporal-varying distortions. Both of these degradation types may reduce the ability for action recognition. These effects become more significant for longer imaging distances and smaller sizes of the objects of interest in the image. The images of objects in imaging through long distance are usually relatively small, and hence, the range of actions that can be resolved is more limited, particularly under strong atmospheric effects. In this study, we perform action localization by first applying optical flow unique processing, and also using a variant of SSD (Single Shot MultiBox Detector) to regress and classify detection boxes in each video frame potentially containing an action of interest.

Paper Details

Date Published: 7 October 2019
PDF: 6 pages
Proc. SPIE 11166, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies III, 111660U (7 October 2019); doi: 10.1117/12.2534670
Show Author Affiliations
Eli Chen, Ben-Gurion Univ. of the Negev (Israel)
Oren Haik, Ben-Gurion Univ. of the Negev (Israel)
Yitzhak Yitzhaky, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 11166:
Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies III
Henri Bouma; Radhakrishna Prabhu; Robert James Stokes; Yitzhak Yitzhaky, Editor(s)

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