Research of Video Surveillance System Base on Face Recognition and Motion Detection

Da Guang Jiang; Jun Kai Yi; Gao Hui Bian

doi:10.4028/www.scientific.net/AMR.271-273.961

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Research of Video Surveillance System Base on Face Recognition and Motion Detection
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273Research of Video Surveillance System Base on Face...

Research of Video Surveillance System Base on Face Recognition and Motion Detection

Abstract:

In this paper, by using skin-color feature, especial location and pixel features of eyes in face area, an efficient face detection algorithm was designed. After face detection, discrete cosine Transform (DCT) was used to extract a set of observation, which is provided to train and recognize faces in the way of Hidden Markov Model (HMM). In order to solve the shortcoming that traditional motion detection algorithm can not be used to detect slow moving objects from an image sequence, an improved method was proposed by rebuilding the background.

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Periodical:

Advanced Materials Research (Volumes 271-273)

Pages:

961-966

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.961

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Online since:

July 2011

Authors:

Da Guang Jiang, Jun Kai Yi, Gao Hui Bian

Keywords:

Background Different, Face Recognition, Hidden Markova Model, Motion Detection, Video Surveillance

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References

[1] Xiao-bo Li and Nicholas Roeder: Face Recognition Extraction From Front View Images[J]. Patten Recognition, 28(8) (1995), pp.1168-1179.

DOI: 10.1016/0031-3203(94)00167-k

Google Scholar

[2] Meng L, Nguyen T Q and Castanon D A: An image-based Bayesian framework for face detection[J]. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Hilton Head Island, South Carolina, USA, (2000), pp.302-307.

DOI: 10.1109/cvpr.2000.855833

Google Scholar

[3] LU Jian and WANG Hui: Comparison Between SVD and DCT Feature Extraction Methods in Face Recognition[J]. Editorial Board of Geomatics and Information Science of Wuhan University, 30(02) (2005), pp.18-19.

Google Scholar

[4] Yang MH, Kriegman and Ahuja N: Detection faces in images: A survey[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 28(1) (2002), pp.34-58.

DOI: 10.1109/34.982883

Google Scholar

[5] Kin-Man Lam and Hong Yan: Location and Extraction the Eye in Human Face Image[J]. Pattern Recognition, 29(5) (1996), pp.771-779.

DOI: 10.1016/0031-3203(95)00119-0

Google Scholar

[6] DAI Ke-xue, LI Guo-hui, TU Dan and YUAN Jian: Prospects and Current Studies on Background Subtraction Techniques for Moving Objects Detection from Surveillance Video [J]. Journal of Image and Graphics, 11(7) (2006), pp.919-920.

Google Scholar