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A method in Curvelet transformation for human detection is proposed in this paper. First, the curvelet coefficient was obtained by conducting the second curvelet transform for images. Then several statistical characteristics were computed from each sub-band coefficient. Finally, according the possibilities of the statistical features chosen by AdaBoost weak classifiers, some reasonable statistical...
An efficient feature extraction method based on the Curvelet Transform for detecting human in static images is proposed in this paper. The edge features can be extracted with the block-based statistical information of each sub-band coefficients, and then the texture feature can be extracted from the co-occurrence of the lowest sub-band coefficients, all the extracted features are concatenated as the...
Doors are important landmarks for indoor mobile robot navigation. Most existing algorithms for door detection use range sensors or work in limited environments because of restricted assumptions about color, pose, or lighting. We present a vision-based door detection algorithm that achieves robustness by utilizing a variety of features, including color, texture, and intensity edges. We introduce two...
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