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Abnormal behavior detection has recently gained growing interest from computer vision researchers. In this paper, the gait-analysis-based abnormal detection is proposed for walking scenes, where gaits of people are analyzed in all kinds of situations and the gait data are utilized to construct the basic gait model. Walking people in the crowd are tracked and their activities silhouettes are abstracted...
Household security becomes more and more important with the growth of aged population. A surveillance robot is a potential solution for this issue. In this paper, we present a novel household surveillance robot with human recognition. Since a master-slaver structure and efficient interfaces are used for its hardware, this robot can always make prompt response to the outside information, even though...
Crowd density estimation is of importance in security monitoring. Many crowd disasters happened because of the loss of control of the crowd density. This paper presents an algorithm to estimate crowd density by employing Markov Random Field (MRF). Three types of image features are extracted for estimating, and they are affected more by the neighboring features than by others, meeting the properties...
The aging of population has become a social problem and fall is a major health risk in the elderly. To this end, this paper presents a novel approach for fall detection applied to an intelligent household surveillance robot. Silhouette based features are extracted, including aspect ratio of minimal bounding box of the human silhouette, approximated elliptical eccentricity, normalized central moments...
Video surveillance in crowded areas is becoming more and more significant for public security. This paper presents a method for the detection of abnormality in crowded scenes based on the crowd motion characteristics. These characteristics includes the crowd kinetic energy and the motion directions. This approach estimates the crowd kinetic energy and the motion directions based on the optical flow...
Crowd control and management is a very important task in public places. Historically, many crowd disasters happened because of the loss of control of the crowd flow direction. This paper presents an intelligent surveillance system based on RANSAC (Random Sample Consensus) algorithm, which can estimate the crowd flow direction and classify people into different crowd groups. We calculate the optical...
In this paper, we present a texture-based multitarget tracking algorithm. Moving objects are described by local binary patterns (LBP), which is a kind of discriminative texture descriptor. The Kalman filter is introduced into the algorithm to predict the blob's new position and size. Blobs are searched in the neighborhood of the Kalman predictions. If more than one are found, the LBP distance, which...
In this paper, an integrated video surveillance system for robust tracking is introduced. In the blob detection part, an optical flow algorithm for crowded environment is studied experimentally and a comparison study with respect to traditional subtraction approach is carried out. In the segmentation part, different algorithms are fused to develop a hybrid algorithm for stable segmentation, and validation...
In many societies, the aged people are often living alone. For the aging population, surveillance in household environments has become more and more important. In this paper, we present a household surveillance robot that can detect abnormal events by utilizing video and audio information. In our approach, moving targets can be detected by the robot with a passive acoustic location device. Then the...
For the aging population, surveillance in household environments has become more and more important. In this paper, we present a household robot that can detect abnormal events by utilizing video and audio information. In our approach, moving targets can be detected by the robot using a passive acoustic location device. The robot then tracks the targets by employing a particle filter algorithm. To...
Video surveillance in crowd is challenging for public security. This paper focuses on the detection of human abnormal behaviors in crowd. The issue is crucial in some special localities and has been less studied. To achieve this goal, this paper defines a crowd energy based on Markov Random Fields. By using wavelet analysis of the energy curves, the crowd status of the scene is detected. After testing...
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