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Human Tracking using Edge and Camera Extracted Pattern Feature for Denser Crowded Videos

M R Sunitha, H S Jayanna, Ramegowda


Human tracking is a major issue in computer vision, with numerous time-critical applications, related to day-to-day activity, have a direct impact on the quality of life. Instantaneous detection of individuals in a real-time scenario is an emerging area of study and many methodologies have been suggested, based on a selection of topographies and algorithms. This paper proposes an innovative solution for tracking humans. The system utilizes a new algorithm, which is formed on the recognition of classical pattern extraction from camera surveillance probes. These extracted patterns can be used to focus on both still and walking person’s moves. Furthermore, the information is fused using a sequential implementation. Quite a lot of experiments illustrated the efficiency of our approach, showing that tracking humans can also be performed within multifaceted enclosed environments.

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