Abstract
Many computer vision applications need motion detection and analysis. In this research, a newly developed feature descriptor is used to find sparse motion vectors. Based on the resulting sparse motion field the camera motion is detected and analyzed. Statistical analysis is performed, based on polar representation of motion vectors. Direction of motion is classified, based on the statistical analysis results. The motion field further is used for depth analysis. This proposed method is evaluated with two video sequences under image deformation: illumination change, blurring and camera movement (i.e. viewpoint change). These video sequences are captured from a moving camera (moving/driving car) with moving objects.
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Desai, A., Lee, DJ., Mody, S. (2015). Automatic Motion Classification for Advanced Driver Assistance Systems. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_77
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DOI: https://doi.org/10.1007/978-3-319-27863-6_77
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