Abstract
Video Surveillance Systems have gained immense popularity in the recent past because of the fact that it can be used in numerous real-world scenario applications. Monitoring the people flow pattern as well as counting them serves as valuable information in many surveillance related applications. In this paper we propose a system that is used for counting the number of people passing through the camera field of view. A single overhead camera is used to get a clear top-view which avoids occlusions. For background subtraction, running Gaussian approach has been used as a preprocessing step, to facilitate the further segmentation and tracking procedures. Connected component analysis is used to group the similar blobs together followed by intensity based correlation for blob matching followed by Kalman tracking. The percentage of blobs that crosses a reference line is recorded. Two counters are incremented depending on the direction of movement of the blobs and the algorithm is able to count the number of people moving up/down the scene.
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Avinash, N., Shashi Kumar, M.S., Sagar, S.M. (2013). Automated Video Surveillance for Retail Store Statistics Generation. In: S, M., Kumar, S. (eds) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 221. Springer, India. https://doi.org/10.1007/978-81-322-0997-3_52
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DOI: https://doi.org/10.1007/978-81-322-0997-3_52
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