Abstract
This paper describes a method for the moving object detection and tracking in video sequences using contourlet transform. For the contourlet transform to be translation-invariant a 2D cycle spinning is implemented on subbands ∆ 1 and ∆ 2. Cycle spinning for edge detection is implemented. The shape of object may change from this frame to other frame. The 3D moving object is combined two parts: a 2D shape change and 2D motion. The 2D motion of the object, we use the minimum Hausdorff distance from the model to the image to find where object moved to. With 2D shape change of the object, we use distance from the image to the transformed model to select set of image pixels of the next model. For performance evaluation, we compared the proposed method based on the contourlet transform using cycle spinning with the similar methods based on the complex wavelet transform and wavelet transform.
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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Thanh Binh, N., Dien, T.A. (2013). Object Detection and Tracking in Contourlet Domain. In: Vinh, P.C., Hung, N.M., Tung, N.T., Suzuki, J. (eds) Context-Aware Systems and Applications. ICCASA 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36642-0_20
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DOI: https://doi.org/10.1007/978-3-642-36642-0_20
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