Study on the cascade classifier in target detection under complex background

Gao Wen; Tang Yang; Zhu Ming

doi:10.7498/aps.63.094204

Abstract

Method of target detection and tracking is one of the hot topics in image processing and computer vision field, which is significant not only in military such as imaging guidance and military target tracking, but also for civil use such as security and monitoring and the intelligent man-machine interaction. Treating the feature matching problem as a more general equinoctial classification question, can turn the intractable high-dimensional problem to a classification problem and deplete computer complexity. This method is based on the law of large numbers and Bayes rule. In this paper we propose a non-hierarchy structure classifier, for which the equation for calculation is theoretically derived, and apply 1bitBP feature to the classifier; and for further reducing the amount of calculation, we use integral image and square integral image to variance classifier as preprocessor, and then use non-hierarchy classifier to handle the patches which meet the variance demand and use the nearest neighbor to further improve the accuracy, and finally realize target detection and tracking based on cascade classifier. Our experimental results show that the method proposed is far superior in calculation amount and processing precision, and is robust to scale changing and rotation, so the method proposed in this paper is of high practical value.

Keywords:

Authors and contacts

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
2.
Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences, Changchun 130033, China
Funds: Project supported by the Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences (Grant No. Y2HC1SR121).

References

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[2]	Guo G R, Wang H Q, Jiang B 2006 Acta Phys. Sin. 55 3985 (in Chinese) [郭桂蓉, 王宏强, 姜斌 2006 55 3985]
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[4]	Zhang J S, Zhang Z T 2010 Chin. Phys. B 19 104601
[5]	Sun J F, Wang Q, Wang L 2010 Chi. Phys. B 19 104203
[6]	CHEN G Y, GUO Z X, ZHANG C P 2003 Chinese Phys. Lett. 20 2161
[7]	YanJ, Wu M Y 2012 Opt. Precision Eng. 20 439 (in Chinese) [颜佳, 吴敏渊 2012 光学精密工程 20 439]
[8]	Zhu Q P, Yan J, Zhang H 2013 Opt. Precision Eng. 21 437 (in Chinese) [朱秋平, 颜佳, 张虎 2013 光学精密工程 21 437]
[9]	Gong J L, He X, Wei Z H 2012 Opt. Precision Eng. 20 413 (in Chinese) [龚俊亮, 何昕, 魏仲慧 2012 光学精密工程 20 413]
[10]	Shi J, Tomasi C 1994 Conf. on Computer Vision and Pattern Recognition, 1994
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[12]	Ross D, Lim J, Lin R S, Yang M H 2008 Int J Comput Vis. 77 125
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[14]	Duarte M F, Baraniuk R G 2012 IEEE Trans. Image Proc. 21 494
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[16]	Chen T, Li Z W, Wang J L, Wang B, Guo S 2012 Opt. Precision Eng. 20 2523 (in Chinese) [陈涛, 李正炜, 王建立, 王斌, 郭爽 2012 光学精密工程 20 2523]
[17]	Lepetit V, Fua P 2006 IEEE Trans. Pattern Analysis and Machine Intelligence, 28 1465
[18]	Grabner H, Leistner C, Bischof H 2008 European Conf. on Computer Vision
[19]	Babenko B, Yang M-H, Belongie S 2009 IEEE Conf. on Computer Vision and Pattern Recognition, Washington, DC 2009 p983
[20]	Viola P, Platt J, Zhang C 2005 Neural Information Processing Systems, 2005
[21]	Saffari A, Leistner C, Santner J 2009 IEEE 12th International Conf. on Computer Vision Workshops Washington DC 2009 p1393
[22]	Leistner C, Saffari A, Bischof H 2010 20th International Conf. on Pattern Recognition, Washington DC 2010 p3545
[23]	Viola P, Jones M, Snow D 2005 I nternational Journal of Computer Vision 63 153
[24]	Tomasz T, Vincent L 2012 European Conf. on Computer Vision (ECCV) 2012
[25]	Breiman L 2001 Machine Learning 45 5
[26]	Kalal Z, Matas J, Mikolajczyk K 2010 Conf. on Computer Vision and Pattern Recognition, 2010
[27]	Viola P, Jones M 2001 Conf. on Computer Vision and Pattern Recognition, 2001 p511
[28]	Zheng F, Webb G 2005 the Fourth Australasian DataMining Conference (AusDM05), Sydney, 2005 p141
[29]	Hoiem D, Sukthankar R, Schneiderman H, Huston L 2004 Conf. on Computer Vision and Pattern Recognition, 2004, 02 p490
[30]	Amit Y, Geman D 1997 Neural Computation, 9 7
[31]	Bay H, Ess A, Tuytelaars T 2008 Computer Vision and Image Understanding 10 346
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Cited By

[1]	Li T W, Shi A G, He S H 2009 Acta Phys. Sin. 58 794 (in Chinese) [李天伟, 石爱国, 何四华 2005 58 794]
[2]	Guo G R, Wang H Q, Jiang B 2006 Acta Phys. Sin. 55 3985 (in Chinese) [郭桂蓉, 王宏强, 姜斌 2006 55 3985]
[3]	Wang M W, Zhai H C, Gao L J 2009 Acta Phys. Sin. 58 1662 (in Chinese) [王明伟, 翟宏琛, 高丽娟 2009 58 1662]
[4]	Zhang J S, Zhang Z T 2010 Chin. Phys. B 19 104601
[5]	Sun J F, Wang Q, Wang L 2010 Chi. Phys. B 19 104203
[6]	CHEN G Y, GUO Z X, ZHANG C P 2003 Chinese Phys. Lett. 20 2161
[7]	YanJ, Wu M Y 2012 Opt. Precision Eng. 20 439 (in Chinese) [颜佳, 吴敏渊 2012 光学精密工程 20 439]
[8]	Zhu Q P, Yan J, Zhang H 2013 Opt. Precision Eng. 21 437 (in Chinese) [朱秋平, 颜佳, 张虎 2013 光学精密工程 21 437]
[9]	Gong J L, He X, Wei Z H 2012 Opt. Precision Eng. 20 413 (in Chinese) [龚俊亮, 何昕, 魏仲慧 2012 光学精密工程 20 413]
[10]	Shi J, Tomasi C 1994 Conf. on Computer Vision and Pattern Recognition, 1994
[11]	Lowe D G 2004 International Journal of Computer Vision 60 91
[12]	Ross D, Lim J, Lin R S, Yang M H 2008 Int J Comput Vis. 77 125
[13]	Ma Y, Lv Q B, Liu Y Y, Qian L L, Pei L L 2013 Acta Phys. Sin. 62 204202 (in Chinese) [马原, 吕群波, 刘扬阳, 钱路路, 裴琳琳 2005 62 204202]
[14]	Duarte M F, Baraniuk R G 2012 IEEE Trans. Image Proc. 21 494
[15]	Shi W J, Li J 2012 Opt. Precision Eng. 20 2095 (in Chinese) [石文轩, 李婕 2012 光学精密工程 20 2095]
[16]	Chen T, Li Z W, Wang J L, Wang B, Guo S 2012 Opt. Precision Eng. 20 2523 (in Chinese) [陈涛, 李正炜, 王建立, 王斌, 郭爽 2012 光学精密工程 20 2523]
[17]	Lepetit V, Fua P 2006 IEEE Trans. Pattern Analysis and Machine Intelligence, 28 1465
[18]	Grabner H, Leistner C, Bischof H 2008 European Conf. on Computer Vision
[19]	Babenko B, Yang M-H, Belongie S 2009 IEEE Conf. on Computer Vision and Pattern Recognition, Washington, DC 2009 p983
[20]	Viola P, Platt J, Zhang C 2005 Neural Information Processing Systems, 2005
[21]	Saffari A, Leistner C, Santner J 2009 IEEE 12th International Conf. on Computer Vision Workshops Washington DC 2009 p1393
[22]	Leistner C, Saffari A, Bischof H 2010 20th International Conf. on Pattern Recognition, Washington DC 2010 p3545
[23]	Viola P, Jones M, Snow D 2005 I nternational Journal of Computer Vision 63 153
[24]	Tomasz T, Vincent L 2012 European Conf. on Computer Vision (ECCV) 2012
[25]	Breiman L 2001 Machine Learning 45 5
[26]	Kalal Z, Matas J, Mikolajczyk K 2010 Conf. on Computer Vision and Pattern Recognition, 2010
[27]	Viola P, Jones M 2001 Conf. on Computer Vision and Pattern Recognition, 2001 p511
[28]	Zheng F, Webb G 2005 the Fourth Australasian DataMining Conference (AusDM05), Sydney, 2005 p141
[29]	Hoiem D, Sukthankar R, Schneiderman H, Huston L 2004 Conf. on Computer Vision and Pattern Recognition, 2004, 02 p490
[30]	Amit Y, Geman D 1997 Neural Computation, 9 7
[31]	Bay H, Ess A, Tuytelaars T 2008 Computer Vision and Image Understanding 10 346
[32]	Stalder S, Grabner H, Gool L V 2009 IEEE 12th International Conf. on Computer Vision Workshops (ICCV) 2009
[33]	Yu Q, Dinh T B, Medioni G 2008 European Conf. on Computer Vision. 2008

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Vol. 63, Issue 9 - 2014-05-05

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