ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Robust background subtraction with shadow and highlight removal for indoor surveillance
EURASIP Journal on Applied Signal Processing
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
Segmentation of soft shadows based on a daylight- and penumbra model
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Graph cut based segmentation of soft shadows for seamless removal and augmentation
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Foreground and shadow segmentation based on a homography-correspondence pair
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
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We present a system for detecting shadows in dynamic outdoor scenes. The technique is based on fusing background subtraction operations performed on both color and disparity data, respectively. A simple geometrical analysis results in an ability to classify pixels into foreground, shadow candidate, and background. The shadow candidates are further refined by analyzing displacements in log chromaticity space to find the shadow hue shift with the strongest data support and ruling out other displacements. This makes the shadow detection robust towards false positives from rain, for example. The techniques employed allow for 3Hz operation on commodity hardware using a commercially available dense stereo camera solution.