Abstract：Moving shadow detection is critical for video surveillance system since shadow points are often misclassified as object points, which causes errors in segmentation and tracking. The conventional algorithms always need the scene characteristics, which makes the algorithms not widely used and automatically performed. An approach is presented that does not rely on any scene assumptions such as camera location and scene characteristics. Color information, texture information and spatial constraints are embedded to define the overall algorithm. Firstly, relevant areas are identified in each image. Then, the color distortion caused by shadow are calculated. Finally, the moving object and shadow are detected by using color distortion compensation and texture verification. The proposed algorithm is demonstrated on many kinds of outdoor video sequences. Moreover, the performance comparisons show that the proposed algorithm outperforms the conventional ones.
[1] Prati A, Mikic I, Trivedi M M, et al. Detecting Moving Shadows: Algorithms and Evaluation. IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(7): 918923 [2] Hsieh J W, Hu W F, Chang C J, et al. Shadow Elimination for Effective Moving Object Detection by Gaussian Shadow Modeling. International Journal of Image and Vision Computing, 2003, 21(6): 505516 [3] Onoguchi K. Shadow Elimination Method for Moving Object Detection // Proc of the 14th International Conference on Pattern Recognition. Brisbane, Australia, 1998, Ⅰ: 583587 [4] Das S, Bhanu B. A System for ModelBased Object Recognition in Perspective Aerial Images. Pattern Recognition, 1998, 31(4): 465491 [5] Nayar S K, Bolle R M. Reflectance Based Object Recognition. International Journal of Computer Vision, 1996, 17(3): 219240 [6] Stander J, Mech R, Ostermann J. Detection of Moving Cast Shadows for Object Segmentation. IEEE Trans on Multimedia, 1999, 1(1): 6576 [7] Mikic I, Cosman P C, Kogut G T, et al. Moving Shadow and Object Detection in Traffic Scenes // Proc of the 15th International Conference on Pattern Recognition. Barcelona, Spain, 2000, Ⅰ: 13211324 [8] Cucchiara R, Grana C, Piccardi M, et al, Sirotti S. Improving Shadow Suppression in Moving Object Detection with HSV Color Information // Proc of the IEEE International Conference on Intelligent Transportation Systems. Oakland, USA, 2001: 334339 [9] Horprasert T, Harwood D, Davis L S. A Statistical Approach for RealTime Robust Background Subtraction and Shadow Detection // Proc of the IEEE International Conference on Computer Vision. Kerkira, Greece, 1999: 119 [10] Shafer S A. Using Color to Separate Reflection Components. Color Research and Application, 1985, 10(4): 210218 [11] Nadimi S, Bhanu B. Physical Models for Moving Shadow and Object Detection in Video. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(8): 10791087 [12] Cavallaro A, Salvador E, Ebrahimi T. ShadowAware ObjectBased Video Processing. Vision, Image and Signal Processing, 2005, 152(4): 398406
2007, Vol. 20 
