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Content Provider | IEEE Xplore Digital Library |
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Author | Rajpurohit, A. Agarwal, A. Gaikwad, M. Garg, K. Inamdar, V. |
Copyright Year | 2012 |
Description | Author affiliation: Department of Computer Science and Information Technology, University of Pune, Maharashtra, India (Rajpurohit, A.; Agarwal, A.; Gaikwad, M.; Garg, K.; Inamdar, V.) |
Abstract | Human motion detection is a fundamental task for many computer vision tasks. In today's competitive environment, the security concerns have grown tremendously. It is imperative for one to be able to safeguard one's property from worldly harms such as thefts, destruction of property, people with malicious intent etc. The most popular method for motion detection is background subtraction where a background model needs to be maintained. In this paper an entropy based method for human motion detection is described which makes no use of background model. The difference image between consecutive images are calculated and at each particular pixel, and a spatial-temporal histogram is generated by accumulating pixels in difference image. This histogram is then normalized to calculate entropy and the magnitude of entropy is used to denote the significance of motion. |
Starting Page | 1 |
Ending Page | 4 |
File Size | 234022 |
Page Count | 4 |
File Format | |
ISBN | 9781467322676 |
e-ISBN | 9781467322690 |
DOI | 10.1109/AICERA.2012.6306742 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-07-19 |
Publisher Place | India |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Histograms Surveillance Crime Streaming media Video monitoring Video surveillance Motion detection Entropy Intelligent algorithms |
Content Type | Text |
Resource Type | Article |
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