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Research Article Open Access
The use of video is becoming prevalent in many applications such as monitoring of traffic, detection of pedestrians, identification of anomalous behaviour in a parking lot or near an ATM, etc. While a single image provides a snapshot of a scene, the different frames of a video taken over time registers the dynamics in the scene, making it possible to capture motion in the sequence. Most of the methods include object segmentation using background subtraction. The tracking strategies use different methodologies like Meanshift, Kalman filter, Particle filter etc. Here, classification of the tracking methods is done, and a detailed description is provided of representative methods in each group. Research works on object detection and tracking in videos. The definition and tasks of object detection and tracking are first described, and the important applications are mentioned.
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Author(s): Suraj Pramod Patil
Meanshift, Kalman filter, Particle filter, Adaptive, Advanced Computing Architectures, Bioinformatics and Computational Biology