Abstract
This paper proposes an improved motion detection method based on the entropy image and the adaptive state-labeling algorithm. In our method, a spatio-temporal sliding window is built for each pixel, and the pixels in the sliding window are assigned state labels according to our adaptive state-labeling technique. The state label distribution in the sliding window is used to construct the entropy image, in which a pixel with lower entropy is considered as part of a moving object In this paper, we have compared our motion detection method with the MRF (Markov random field) based method, the STEI (spatio-temporal entropy image) method, and the DSTEI (difference-based spatio-temporal entropy image) method. Experimental results show that our motion detection method is robust and has lower computational complexity.
| Original language | English |
|---|---|
| Article number | 4253476 |
| Pages (from-to) | 3667-3670 |
| Number of pages | 4 |
| Journal | Proceedings - IEEE International Symposium on Circuits and Systems |
| Publication status | Published - 2007 Sep 27 |
| Event | 2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States Duration: 2007 May 27 → 2007 May 30 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
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Motion detection by using entropy image and adaptive state-labeling technique. / Chang, Meng Chou; Cheng, Yong Jie.
In: Proceedings - IEEE International Symposium on Circuits and Systems, 27.09.2007, p. 3667-3670.Research output: Contribution to journal › Conference article
TY - JOUR
T1 - Motion detection by using entropy image and adaptive state-labeling technique
AU - Chang, Meng Chou
AU - Cheng, Yong Jie
PY - 2007/9/27
Y1 - 2007/9/27
N2 - This paper proposes an improved motion detection method based on the entropy image and the adaptive state-labeling algorithm. In our method, a spatio-temporal sliding window is built for each pixel, and the pixels in the sliding window are assigned state labels according to our adaptive state-labeling technique. The state label distribution in the sliding window is used to construct the entropy image, in which a pixel with lower entropy is considered as part of a moving object In this paper, we have compared our motion detection method with the MRF (Markov random field) based method, the STEI (spatio-temporal entropy image) method, and the DSTEI (difference-based spatio-temporal entropy image) method. Experimental results show that our motion detection method is robust and has lower computational complexity.
AB - This paper proposes an improved motion detection method based on the entropy image and the adaptive state-labeling algorithm. In our method, a spatio-temporal sliding window is built for each pixel, and the pixels in the sliding window are assigned state labels according to our adaptive state-labeling technique. The state label distribution in the sliding window is used to construct the entropy image, in which a pixel with lower entropy is considered as part of a moving object In this paper, we have compared our motion detection method with the MRF (Markov random field) based method, the STEI (spatio-temporal entropy image) method, and the DSTEI (difference-based spatio-temporal entropy image) method. Experimental results show that our motion detection method is robust and has lower computational complexity.
UR - http://www.scopus.com/inward/record.url?scp=34548828268&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34548828268&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:34548828268
SP - 3667
EP - 3670
JO - Proceedings - IEEE International Symposium on Circuits and Systems
JF - Proceedings - IEEE International Symposium on Circuits and Systems
SN - 0271-4310
M1 - 4253476
ER -