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Moving Object Detection and Tracking in Videos

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Performance Evaluation Software

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

Abstract

This chapter provides four sections. The first section introduces the moving object D&T infrastructure and basis of some methods for object detection and tracking (D&T) in videos. In object D&T applications, there is manual or automatic D&T process. Also, the image features, such as color, shape, texture, contours, and motion can be used to track the moving object(s) in videos. The detailed information for moving object detection and well-known trackers are presented in this section as well. In second section, the background subtraction (BS) method and its applications are given in details. The third section declares the details for Mean-shift (MS), Mean-shift filtering (MSF), and continuously adaptive Mean-shift (CMS or CAMShift) methods and their applications. In fourth section, the details for the optical flow (OF), the corner detection through feature points, and OF-based trackers are given in details.

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Correspondence to Bahadir Karasulu .

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Karasulu, B., Korukoglu, S. (2013). Moving Object Detection and Tracking in Videos. In: Performance Evaluation Software. SpringerBriefs in Computer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6534-8_2

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  • DOI: https://doi.org/10.1007/978-1-4614-6534-8_2

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-6533-1

  • Online ISBN: 978-1-4614-6534-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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