Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital photography with flash and no-flash image pairs
ACM SIGGRAPH 2004 Papers
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
Building Illumination Coherent 3D Models of Large-Scale Outdoor Scenes
International Journal of Computer Vision
Shadow detection in colour high-resolution satellite images
International Journal of Remote Sensing
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
Tricolor attenuation model for shadow detection
IEEE Transactions on Image Processing
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Shadows are a frequent occurrence, but they cannot be infallibly recognized until a scene's geometry and lighting are known. We present a number of cues which together strongly suggest the identification of a shadow and which can be examined with low cost. The techniques are: a color image segmentation method that recovers single material surfaces as single image regions irregardless of the surface partially in shadow, a method to recover the penumbra and umbra of shadow; a method for determining whether some object could be obstructing a light source. The last cue requires the examination of well understood shadows in the scene. Our observer is equipped with an extendable probe for casting its own shadows. Actively obtained shadows allow the observer to experimentally determine the location of the light sources in the scene. The system has been tested both indoors and out.