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This paper presents a novel and robust descriptor, depth-projection-map-based bag of contour fragments, which is applied to extraction of hand shape and structure information from depth maps. Our method projects depth maps onto three orthogonal planes to generate the depth projection maps. Then, the bag of contour fragment descriptors are extracted from the three depth projection maps and concatenated...
In this paper, we aim to address the issue that semi-supervised learning is prone to be influenced by the quality and quantity of initial seeds. In order to expand the initial labeled data, we select credible samples from unlabeled data by a proposed bilateral latent information miner. The miner can extract information from unlabeled data for both positive and negative class respectively. Then we...
This paper presents an enhanced version of descriptor DPM-BCF (Depth Projection Maps-based Bag of Contour Fragments). Named as eDPM, it modified the projection method by converting the depth cloud into three grayscale projected maps in three orthogonal planes. Then we extract Bag of Contour Fragments (BCF) descriptor and Histogram of Oriented Gradient (HOG) descriptor from the three grayscale projected...
One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several...
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