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- W2894428579 abstract "Daily experience tells us that human visual systems are very fast and intuitively recognize and track objects around us. Real-time detection and tracking of a changeable number of objects is of high interest for several applications such as visual surveillance, traffic monitoring, human computer interaction etc. This paper presents a novel method for real time object detection using background learning and tracking by proximity analysis of the moving objects. We present our system for multiple moving object detection and tracking using webcam installed inside a building that monitors a typical open work area like lab, hospital or parking area. Object detection is the first and most important step of moving object tracking. Two main processes are implemented in this system. The first process used a simple technique to extract initial background model from first N frame taken from the camera sensors. This helps in detecting moving objects from background. The second process continuously updates the incoming frame for object depending upon the proximity analyses to check whether he object is old, new or removed from the frame sequence with respect to the background. Videos from webcam in indoor and outdoor environments are used to generate the result. We have implemented a new method of multiple objects tracking by using proximity rules of grouping for handling the general problem of multiple moving objects, in various environmental conditions." @default.
- W2894428579 created "2018-10-05" @default.
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- W2894428579 date "2017-05-31" @default.
- W2894428579 modified "2023-09-26" @default.
- W2894428579 title "Real-Time Tracking of Multiple Moving Objects in Video Using Proximity" @default.
- W2894428579 hasPublicationYear "2017" @default.
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