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This work describes a method for accurately tracking persons in indoor surveillance video stream obtained from a static camera with difficult scene properties including illumination changes and solves the major occlusion problem. First, moving objects are precisely extracted by determining its motion, for further processing. The scene illumination changes are averaged to obtain the accurate moving...
Traditional background subtraction methods perform poorly at night. In this paper, a robust method is proposed for automatic visual surveillance in low-light level environment which has quality problems of low brightness, low contrast and high-level noise. The novel method includes techniques of illumination compensation and illumination-invariant background subtraction to solve the low-quality problem...
This paper is concerned with investigating, experiencing, and validating some non classic techniques for compound moving objects analysis in successive video frames. This composite-tasks problem has so far been very`rarely' dealt with as a `single' multidirectional problem, it has always been handled as several separate unidirectional, or seldom bidirectional problems. The paper exhibits an HCI system...
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient...
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