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Surveillance cameras have been widely used in different scenes. Accordingly, a demanding need is to recognize a person under different cameras, which is called person re-identification. This topic has gained increasing interests in computer vision recently. However, less attention has been paid to video-based approaches, compared with image-based ones. Two steps are usually involved in previous approaches,...
Extracting main object from photos is prerequisite for image processing and semantic image understanding in many areas especially in multimedia signal processing at internet. So far, either human interaction in single image or sequence image frames are required for the extraction and most of them still rely on hand-crafted features. In contrast, the proposed work cast the human boundary detection...
Activity recognition is one of the most challenging problems in the video-based surveillance and computer-vision. In this paper we propose a novel approach to recognize human activity in which we decompose an activity into multiple stochastic processes, each corresponding to one scale of motion details. We present a hierarchical durational-state dynamic Bayesian network(HDS-DBN) to model two stochastic...
A rail surface defects inspection method based on automated machine vision system is proposed in the paper. Two kinds of defect images including spalling of rail head and cracks in surface are analyzed with this method. Some related algorithms comprising denoising, image segmentation and feature extraction are applied in processing the images of rail surface defect. Then accurate region of defect...
Corner detection is an important step in the image processing of machine vision. An improved algorithm is proposed in this paper following the analysis on the existing corner detection algorithms and on the localization precision and computation efficiency in the Harris corner detection algorithm. In this algorithm, a large number of irrelevant points are rejected by statistical analyzing the pixel...
Many existing approaches in computer vision to pose estimation make simplifications of the measurement problem, either using silhouettes or assuming knowledge of appearance or color. However, recognizing the pose of a person who is persistently under cover remains challenging. We present a real time monocular-video approach for markerless pose estimation of human body under cover without manual initialization...
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