Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Hierarchical Approach to Robust Background Subtraction using Color and Gradient Information
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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PCB inspection for missing or misaligned components using background subtraction
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Shadow Detection in Dynamic Scenes Using Dense Stereo Information and an Outdoor Illumination Model
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
RVM-based human action classification in crowd through projection and star skeletonization
Journal on Image and Video Processing - Special issue on video-based modeling, analysis, and recognition of human motion
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This work describes a robust background subtraction scheme involving shadow and highlight removal for indoor environmental surveillance. Foreground regions can be precisely extracted by the proposed scheme despite illumination variations and dynamic background. The Gaussian mixture model (GMM) is applied to construct a color-based probabilistic background model (CBM). Based on CBM, the short-term color-based background model (STCBM) and the long-term color-based background model (LTCBM) can be extracted and applied to build the gradient-based version of the probabilistic background model (GBM). Furthermore, a new dynamic cone-shape boundary in the RGB color space, called a cone-shape illumination model (CSIM), is proposed to distinguish pixels among shadow, highlight, and foreground. A novel scheme combining the CBM, GBM, and CSIM is proposed to determine the background which can be used to detect abnormal conditions. The effectiveness of the proposed method is demonstrated via experiments with several video clips collected in a complex indoor environment.