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We here present a multi-sensor data fusion architecture that takes into account the performance of video sensors in detecting moving targets for video surveillance purposes. Target detection and tracking is performed via classification by an ensemble of classifiers learned online using heterogeneous features for each target. A novel approach is then used to estimate the position of the target on the...
Motion classification is the first step of gait recognition. The classification of motion is conducted, and behavior validity can be made under specific scenarios. In order to identify people movement in an intelligent security monitoring system, moving body is detected and the boundary is extracted. The paper proposes a complex number notation based on centroid in order to indicate a pedestrian's...
Many computer vision systems try to infer semantic information about a video scene content by looking at the time series of the silhouettes of the moving objects. This paper proposes a new inter-frame feature set (signature) based on piecewise surfacic descriptions of binary silhouettes. It captures the dynamics of moving objects and compacts it into a robust set of features suitable for classification...
Many studies have now shown that it is possible to recognize people by the way they walk. As yet there has been little formal study of people recognition using the kinematic-related gait features. We present a new method for gait recognition using dynamic features including the angular measurements of the lower limbs as well as the spatial displacement of the trunk. Gait signatures are derived using...
For intelligent surveillance, one of the major tasks to achieve is to recognize activities present in the scene of interest. Human subjects are the most important elements in a surveillance system and it is crucial to classify human actions. In this paper, we tackle the problem of classifying human actions as running or walking in videos. We propose using local temporal features extracted from rectangular...
A new classification approach for human body postures based on a neural fuzzy network is proposed in this paper, and the approach is applied to detect emergencies that are caused by accidental falls. Four main body postures are used for posture classification, including standing, bending, sitting, and lying. After the human body is segmented from the background, the classification features are extracted...
Multi-agent interactions often result in mutual occlusion sequences which constitute a visual signature for the event. We define six qualitative occlusion primitives based on the persistence hypothesis (objects continue to exist even when hidden from view): isolated, occlude with foreground, occlude by background, disappear, enter and exit. Variable length temporal sequences of occlusion primitives...
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