Titlebook: Computer Vision - ECCV 2008; 10th European Confer David Forsyth,Philip Torr,Andrew Zisserman Conference proceedings 2008 Springer-Verlag Be

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Segmentation and Recognition Using Structure from Motion Point Cloudscific patterns of motion and 3D world structure that vary with object category. We introduce features that project the 3D cues back to the 2D image plane while modeling spatial layout and context. A randomized decision forest combines many such features to achieve a coherent 2D segmentation and reco

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Localizing Objects with Smart Dictionariesbrute-force approach made feasible by three key developments: First, our method reduces the size of a large generic dictionary (on the order of ten thousand words) to the low hundreds while increasing classification performance compared to .-means. This is achieved by creating a discriminative dicti

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Weakly Supervised Object Localization with Stable Segmentations suited for the task of learning object classifiers from weakly labeled image data, where only the presence of an object in an image is known, but not its location. Some recent work has explored the application of MIL algorithms to the tasks of image categorization and natural scene classification.

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A Perceptual Comparison of Distance Measures for Color Constancy Algorithmster vision. As many color constancy algorithms exist, different distance measures are used to compute their accuracy. In general, these distances measures are based on mathematical principles such as the angular error and Euclidean distance. However, it is unknown to what extent these distance measu