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This paper proposes a method for human detection in crowded scene from static images. We introduce to combine edgelet and LBP features to obtain more discriminative representations for local area. To cope with partial occlusion, part detectors are learned using real AdaBoost in bootstrap way. Responses of part detectors are combined to form the final results. We test our approach on several common...
With the increasing amount of surveillance data, moving object segmentation in the compressed domain has drawn broad attention from both academy and industry. In this paper, we propose a novel moving object segmentation method towards H.264 compressed surveillance videos. First, the motion vectors (MV) are accumulated and filtered to achieve reliable motion information. Second, considering the spatial...
Human action recognition is a challenge problem in computer vision. In this paper, we propose an improved approach using kinematic features for action recognition. In this approach, we find the area that relates to action by a simple method, and select eight discriminative features derived from optical flow field to describe the dynamics of the field. The covariance matrix of the feature vectors is...
In this paper, we propose an efficient luggage searching system based on image classification and retrieval. In this system, we can register and retrieve the luggage automatically. We bring in classification to register images so as to increase the retrieval speed. The Block HSV histogram and the scale invariant feature transform (SIFT) are used for image retrieval. Experiments show that the proposed...
Paper currency recognition with good accuracy and high processing speed has great importance for banking system. How to extract high quality monetary features from currency images is a key problem in paper currency recognition. Based on the traditional local binary pattern (LBP) method, an improved LBP algorithm, called block-LBP algorithm, is proposed in this paper for characteristic extraction....
We propose a novel relative orientation feature (ROF) to represent the contour or skeleton of a two-dimensional object. With the aid of ROF, the shapes of two objects with fine structures can be compared. Matching with ROF is invariant with respect to translation, rotation and scaling transforms. Experimental results on hand gesture recognition demonstrate the effectiveness and efficiency of ROF with...
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