A development of content-based video summarization system using machine-learning and its application to analysis of livestock behavior

Que Zhi; Tomoko Saitoh; Mizuki Nakajima; Tsuyoshi Saitoh

doi:10.1117/12.2522172

22 March 2019 A development of content-based video summarization system using machine-learning and its application to analysis of livestock behavior

Que Zhi, Tomoko Saitoh, Mizuki Nakajima, Tsuyoshi Saitoh

Author Affiliations +

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 1104911 (2019) https://doi.org/10.1117/12.2522172
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

In this work, we propose a static video summarization approach for the analysis of cattle's movement. An original digital video with a length of about 1 hour (58 minutes and 42 seconds) recording the daily behaviors of cattle in cattle barn was applied as the experimental object. In the approach, machine learning, statistics and color histogram are used to extract key-frames from the video. And it can be confirmed that this approach achieve the purpose of video summarization based on cattle's movement through analyzing the results of the experiment.

Citation Download Citation

Que Zhi, Tomoko Saitoh, Mizuki Nakajima, and Tsuyoshi Saitoh "A development of content-based video summarization system using machine-learning and its application to analysis of livestock behavior", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104911 (22 March 2019); https://doi.org/10.1117/12.2522172

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