Cast shadow detection for moving objects based on binocular stereo vision

Abstract

A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations.

Keywords

cast shadow detection / stereo vision / moving objects / flat ground

References

[1] RaoB, ZhengG, ChenT-m, HuangJ, ShaoXin. An efficient hierarchical method for image shadow detection [C]. Proceedings of 2nd International Workshop on Knowledge Discovery and Data Mining, 2009, Piscataway, IEEE: 622-627

[2] SALVADOR E. Shadow segmentation and tracking in real world conditions [EB/OL]. [2012-08-01]. http://biblion.epfl.ch/EPFL/theses/2004/3076/EPFLTH3076.pdf.

[3] PratiA, MikicI, TrivediM M, CucchiaraR. Detecting moving shadows: Algorithms and evaluation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(7): 918-923

[4] NadimiS, BhanuB. Physical models for moving shadow and object detection in video [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(8): 1079-1087

[5] WangC-x, ZhangW-juan. A robust algorithm for shadow removal of foreground detection in video surveillance [C]. Proceedings of 2009 Asia-Pacific Conference on Information Processing, 2009, Piscataway, IEEE: 422-425

[6] GudmundssonK S, AwwalA A S, CagatinF S. Shadow extraction [C]. Proceedings of SPIE, 2008, Bellingham, SPIE: 70720U-70720U-9

[7] KollerD, DanilidisK, NagelH H. Model-based object tracking in monocular image sequences of road traffic scenes [J]. International Journal of Computer Vision, 1993, 10(3): 257-281

[8] SialaK, ChakchoukM, BesbesO, ChaiebF. Moving shadow detection with support vector domain description in the color ratios space [C]. Proceedings of the 17th International Conference on Pattern Recognition, 2004, Piscataway, IEEE: 384-387

[9] Martel-brissonN, ZaccarinA. Learning and removing cast shadows through a multidistribution approach [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(7): 1133-1146

[10] WangY, LoeK F, WuJ-kang. A dynamic conditional random field model for foreground and shadow segmentation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(2): 279-289

[11] CucchiaraR, GranaC, PiccardiM, PratiA, SirottiS. Improving shadow suppression in moving object detection with HSV color information [C]. IEEE Conference on Intelligent Transportation Systems, 2001, Piscataway, IEEE: 334-339

[12] LeoneA, DistanteC. Shadow detection for moving objects based on texture analysis [J]. Pattern Recognition, 2007, 40(4): 1222-1233

[13] ZhangW, FangX-z, YangX-k, WuQ M J. Moving cast shadows detection using ratio edge [J]. IEEE Transactions on Multimedia, 2007, 9(6): 1202-1213

[14] YangM T, LoK H, ChiangC C, TaiW K. Moving cast shadow detection by exploiting multiple cues [J]. IET Image Processing, 2008, 2(2): 95-104

[15] XuD, LiX-l, LiuZ-k, YuanYuan. Cast shadow detection in video segmentation [J]. Pattern Recognition Letters, 2005, 26(1): 91-99

[16] ElhabianS Y, El-sayedK M, AhmedS H. Moving object detection in spatial domain using background removal techniques-state-of-art [J]. Recent Patents Computer Science, 2008, 1(1): 32-54

[17] BenedekC, SziranyiT. Study on color space selection for detecting cast shadows in video surveillance [J]. International Journal of Imaging Systems and Technology, 2007, 17(3): 190-201

[18] HouY-j, GongS-rong. Adaptive shadows detection algorithm based on Gaussian mixture model [C]. Proceedings of 2008 International Symposium on Information Science and Engineering, 2008, Piscataway, IEEE: 116-120

[19] MACEVOY B. Modern color models [EB/OL]. [2012-08-01]. http://www.handprint.com/HP/WCL/color7.html.