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In recent years, a content-based method such as `bag-of-features' (BoF) is coming to the fore as an object recognition and classification technique. This paper proposes a BoF signature using invariant region descriptor for object retrieval. The region descriptors are extracted from dense sampled regions in the training images. These descriptors are quantized by hierarchical k-means clustering in a...
This work proposes a compositional approach to hand posture recognition, using sparse features. The hand posture is decomposed into relevant compositions which are learned for each hand posture class without supervision; no hand segmentations or localization during training is needed. To learn relevant composition prototypes, an entropy range maximization loop was introduced, by performing k-means...
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