Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2004.1334362
Title: Kernel-based method for tracking objects with rotation and translation
Authors: Zhang, H.
Huang, Z. 
Huang, W.
Li, L.
Issue Date: 2004
Source: Zhang, H., Huang, Z., Huang, W., Li, L. (2004). Kernel-based method for tracking objects with rotation and translation. Proceedings - International Conference on Pattern Recognition 2 : 728-731. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2004.1334362
Abstract: This paper addresses the issue of tracking translation and rotation simultaneously. Starting with a kernel-based spatial-spectral model for object representation, we define an l 2-norm similarity measure between the target object and the observation, and derive a new formulation to the tracking of translational and rotational object. Based on the tracking formulation, an iterative procedure is proposed. We also develop an adaptive kernel model to cope with varying appearance. Experimental results are presented for both synthetic data and real-world traffic video.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/39955
ISBN: 0769521282
ISSN: 10514651
DOI: 10.1109/ICPR.2004.1334362
Appears in Collections:Staff Publications

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