We address the issue of markless human motion capture by voxel labeling. We explore the problem of pose estimation from voxel cloud based on a predefined human model. First, voxels are labeled into different individua...
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ISBN:
(纸本)9780769552378;9780769538839
We address the issue of markless human motion capture by voxel labeling. We explore the problem of pose estimation from voxel cloud based on a predefined human model. First, voxels are labeled into different individual parts of the body. Then, the joints are extracted from labeled voxels. Finally, the joint angles are estimated from the joints. Tested on the voxel data in our experiments, our algorithm is insensitive to noise and achieve fine accuracy in pose estimation.
B-factor reflects the atom's uncertainty about its average position within a crystal structure and is highly correlated with protein functions. In this article, we propose a novel approach to predict the real valu...
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B-factor reflects the atom's uncertainty about its average position within a crystal structure and is highly correlated with protein functions. In this article, we propose a novel approach to predict the real value of B-factor. We firstly extract features from the protein sequences and their evolution information, then apply random forest tree to select the important features, which are further inputted to a two-stage support vector regression (SVR) for prediction. Our results have revealed that a systematic analysis of the importance of different features makes us have deep insights into the different contributions of features and is very necessary for developing effective B-factor prediction tools. We thus develop an online Web server, which is freely available at http://***/bioinf/PredBF for academic use.
This paper is about a vision-based system that automatically monitors intermodal freight trains for the quality of how the loads (containers) are placed along the train. An accurate and robust algorithm to segment the...
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Human matching between different fields of view is a difficult problem in intelligent video surveillance;whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it i...
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Curve matching is one of key issues in computer vision, image analysis and patternrecognition. Based on discrete V-transform, the distance is calculated between curves using the descriptor of V-system to find the mat...
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Curve matching is one of key issues in computer vision, image analysis and patternrecognition. Based on discrete V-transform, the distance is calculated between curves using the descriptor of V-system to find the matching curves, and then the matching parameters are evaluated in this article. The new approach can find efficiently the rough location of a short extracted image curve in a long reference curve. Different from the existing approaches, it needn't to extract feature points. Extensive tests show that it is efficient.
Detecting multi-view faces is a challenging task, not only because of the face variations in scale, illumination, and expression, but also of the variations caused by multiple views. In this paper, we proposed a multi...
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Detecting multi-view faces is a challenging task, not only because of the face variations in scale, illumination, and expression, but also of the variations caused by multiple views. In this paper, we proposed a multi-layer cascaded architecture, which can focus attention on the promising regions of the image. The whole classifiers are only evaluated on the face like parts of the image, while the most amount of background blocks are excluded by the first few layers of the detector. Instead of using predefined priori knowledge about face view partition, we divide the sample space automatically by the branching competitive learning network at different discriminative resolutions. To maintain the high detection efficiency, we adopt the simplified Support Vector Machines (SVMs), called the mirror pair of points (MPP) classifiers, as the component of our detection system. Experimental results show that our system is competitive with other systems presented recently in the literature.
with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images as...
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with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images associated with speckle noise. In this paper, an improved watershed segmentation scheme is proposed based on comprehensive consideration of gray scale information, edge information and the relationship between neighboring regions of ultrasound images. A novel criteria deciding the relationship between neighboring regions was defined, and edge information was also added to the merging guidelines. Similar region merging was then applied to the initial segmentation results. The proposed scheme was tested using representative ultrasound image. The experimental results show that the proposed scheme can produce accurate contours and overcome the over-segmentation phenomenon availably.
In this paper, a novel curve reconstruction method based on A* algorithm from a set of dense scattered points was proposed. Our method can not only reconstruct dense scattered points with single connected complicated ...
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In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and con...
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ISBN:
(纸本)9781424445004
In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov random field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images.
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