Abstract
This paper proposes a real-time objects segmentation and tracking module from video sequences, which can be effectively used in real-time object recognition systems. The module is based on background subtraction method in combination with CAMshift (Continuously Adaptive Mean shift) algorithm. In the first step, background subtraction method is applied to determine pixels of moving objects in video stream. Then, foreground pixels are used as starting point for CAMshift algorithm. CAMshift finds optimal size, position and orientation of moving objects. After that, key frame extraction method is applied in order to choose only relevant frame in later objects classification.
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Acknowledgments
The work presented in the paper was supported by the University Science Park of the University of Zilina (ITMS: 26220220184) supported by the Research &Development Operational Program funded by the European Regional Development Fund and EUREKA project no. E! 6752—DETECTGAME: R&D for Integrated Artificial Intelligent System for Detecting the Wildlife Migration.
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Matuska, S., Hudec, R., Benco, M., Kamencay, P. (2016). Real-Time Segmentation and Tracking Module of Target of Interest from Video Sequence in Object Recognition Systems. In: Sulaiman, H., Othman, M., Othman, M., Rahim, Y., Pee, N. (eds) Advanced Computer and Communication Engineering Technology. Lecture Notes in Electrical Engineering, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-319-24584-3_48
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DOI: https://doi.org/10.1007/978-3-319-24584-3_48
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