Abstract
This chapter describes an original contribute of this book: a method to solve the correspondence problem in multi-camera systems without the assumption of epipolar geometry. This method is suitable to reduce the sensory gap and the problem of the presence of mutual occlusions among moving objects inside a scene. Using this method it is possible to improve the performance of the tracking algorithm. The chapter starts with a brief problem overview and then it presents a description of the epipolar geometry. Finally the proposed solution is described and the final considerations are reported.
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© 2013 Springer Science+Business Media New York
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Amato, A., Di Lecce, V., Piuri, V. (2013). Sensor Data Interpretation for Symbolic Analysis. In: Semantic Analysis and Understanding of Human Behavior in Video Streaming. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5486-1_4
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DOI: https://doi.org/10.1007/978-1-4614-5486-1_4
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-5485-4
Online ISBN: 978-1-4614-5486-1
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