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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...
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...
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...
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...
This paper presents an automatic method to detect abnormal crowd density by using texture analysis and learning, which is very important for the intelligent surveillance system in public places. By using the perspective projection model, a series of multi-resolution image cells are generated to make better density estimation in the crowded scene. The cell size is normalized to obtain a uniform representation...
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