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Skin detection is the preliminary stage of many computer vision applications. In this paper, a statistical fusion model is proposed for detecting skin regions in arbitrary images. We used conditional random field (CRF) to statistically combine the information of different color spaces and model the spatial relationship between image pixels. The conditional probability distribution of labels (skin...
Detecting anomalies in the Traffic Control Systems (TCS) could be very useful for the accident analysis, fault detection and other traffic-related topics. In this article we propose a general framework for the trajectory-based anomaly detection, which is fast and reliable. Experimental results show that the system could be used on a vast variety of camera types and configurations. We have used a semi-supervised...
Automatic vehicle Make and Model Recognition (MMR) system offers a competent way to vehicle classification and recognition systems. This paper proposes a real time while robust vehicle make and model recognition system extracting the vehicle sub-image from the background and studies some sparse feature coding methods such as Orthogonal Matching Pursuit (OMP), some variation of Sparse Coding (SC) methods...
In this paper we propose an efficient method for behavior recognition and identification of anomalous behavior in video surveillance data. This approach consists of two phases of training and testing. In the training phase, first, we use background subtraction method to extract the moving pixels. Then optical flow vectors are extracted for moving pixels. We propose behavior features of each pixel...
Texture classification is an important part of many object recognition algorithms. In this paper, a new approach to texture classification is proposed. Recently, local binary pattern (LBP) has been widely used in texture classification. In conventional LBP, directional statistical features and color information are not considered. To extract color information of textures, we have used color LBP. Also,...
A local-spatial interest point matching algorithm for articulated human upper body tracking application is proposed in this paper. The first stage finds confidently matched pairs of interest points from the reference and target interest point lists through a local-feature-descriptors-based matching method. Applying two cross-checking and displacement-checking steps reduces the number of mismatched...
Tracking failure is an inevitable problem in any object tracking algorithm. Online evaluation of a tracking algorithm to detect and correct failures is therefore an important task in any object tracking system. In this paper we propose an early tracking failure detection procedure for the Continuously Adaptive Mean-Shift(CAMShift) tracking algorithm. We also propose an algorithm to modify the tracker...
Visual sensors, active or passive, play an important role in computer vision and in visual sensors, calibration is of utmost importance. Kinect as a new developed sensor for use as a Natural User Interface is being utilized in different fields especially CV. This integrated system beside other sensors, contains two visual sensors of active and passive that demands a process of calibration. Among different...
Human action recognition is the process of labeling videos contain human motion with action classes. The run time complexity is one of the most important challenges in action recognition. In this paper, we address this problem using video abstraction techniques including key-frame extraction and video skimming. At first we extract key-frames and then skim the video clip by concatenating excerpts around...
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