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Object segmentation and key-pose based summarization for motion video

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Abstract

This paper proposes a key-pose based video summarization system for a video shot facilitated by using a video object segmentation method. Firstly, we detect the camera motion and extract video objects by a 3D graph-based algorithm. Once the objects are obtained, each of them is represented by a shape descriptor. Secondly, in order to find representative frames which preserve scene content as much accurately as possible, the proposed method calculates difference between pairs of frames based on shape descriptors of objects in the video shot. Finally, key-poses (representative frames) are extracted in a global manner by clustering these shapes. Experimental results on motion video shots show that the proposed method outputs satisfactory summarizations.

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Notes

  1. In our paper, the terms of “pose”, “shape”, and “object” are used in a broad sense. They have the same meaning.

  2. http://www.maths.lth.se/matematiklth/personal/petter/surfmex.php

  3. Given a video, motion includes global motion caused by moving camera and local motion caused by moving objects.

  4. See the “bwlabel” function in the MATLAB Image Processing Toolbox.

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Acknowledgements

This work was supported in part by the National Basic Research Program of China (973 Program) under Grant No. 2010CB327902, and the NSFC Nos. 90920301, 61273252, and 61175010.

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Authors and Affiliations

  1. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, 710049, China

    Zhiqiang Tian, Jianru Xue, Xuguang Lan, Ce Li & Nanning Zheng

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Tian, Z., Xue, J., Lan, X. et al. Object segmentation and key-pose based summarization for motion video. Multimed Tools Appl 72, 1773–1802 (2014). https://doi.org/10.1007/s11042-013-1488-7

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