Detection of Objects Temporally Stop Moving with Spatio-Temporal Segmentation 


Vol. 40,  No. 1, pp. 142-151, Jan.  2015


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  Abstract

This paper proposes a method for detection of objects temporally stop moving in video sequences taken by a moving camera. Even though the consequence of missed detection of those objects could be catastrophic in terms of application level requirements, not much attention has been paid in conventional approaches. In the proposed method, we introduce cues for consistent detection and tracking of objects: motion potential, position potential, and color distribution similarity. Integration of the three cues in the graph-cut algorithm makes possible to detect objects that temporally stop moving and are newly appearing. Experiment results prove that the proposed method can not only detect moving objects but also track objects stop moving.

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  Cite this article

[IEEE Style]

D. Kim and G. Kim, "Detection of Objects Temporally Stop Moving with Spatio-Temporal Segmentation," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 1, pp. 142-151, 2015. DOI: .

[ACM Style]

Do-Hyung Kim and Gyeong-Hwan Kim. 2015. Detection of Objects Temporally Stop Moving with Spatio-Temporal Segmentation. The Journal of Korean Institute of Communications and Information Sciences, 40, 1, (2015), 142-151. DOI: .

[KICS Style]

Do-Hyung Kim and Gyeong-Hwan Kim, "Detection of Objects Temporally Stop Moving with Spatio-Temporal Segmentation," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 1, pp. 142-151, 1. 2015.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880