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- W2374111 abstract "We present a discriminative Hough transform based object detector where each local part casts a weighted vote for the possible locations of the object center. We formulate such an object model with an ensemble of randomized trees trained by splitting tree nodes so as to lessen the variance of object location and the entropy of class label. Hough forests can be regarded as task-adapted codebooks of local appearance that allow fast supervised training and fast matching. Experimental results demonstrate that our method has a significant improvement. Compared to other approach such as implicit shape models, Hough forests improve the performance for hands detection on a categorical level." @default.
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- W2374111 date "2012-01-01" @default.
- W2374111 modified "2023-09-25" @default.
- W2374111 title "A New Method for Hand Detection Based on Hough Forest" @default.
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- W2374111 doi "https://doi.org/10.1007/978-3-642-31362-2_12" @default.
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