IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Edge and Corner Detection by Photometric Quasi-Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Classifying color edges in video into shadow-geometry, highlight, or material transitions
IEEE Transactions on Multimedia
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The detection of shadow and shading edges is a first step towards reducing the imaging effects that are caused by interactions of the light source with surfaces that are in the scene. As most of the algorithms for shadow edge detection use photometric information, geometric information have been ignored so far. In this paper, the aim is to include geometric features for more robust shadow edge detection. First, thousands of patches are annotated as either containing a shadow edge or not. Then, geometric features of these patches are analyzed and it is shown that the combination of photometric and geometric features improves the classification of shadow edges with respect to using either one of these features with 14%. These results demonstrate the added value of geometric features, in addition to photometric features, for the detection of shadow edges.