Abstract
This paper presents a new Bayesian face tracking method under particle filter framework. First, two adaptive feature models are proposed to extract face features from image sequences. Then the robustness of face tracking is reinforced via building a local dual closed loop model (LDCLM). Meanwhile, trajectory analysis, which helps to avoid unnecessary restarting of detection module, is introduced to keep tracked faces’ identity as consistent as possible. Experimental results demonstrate the efficacy of our method.
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Yao, D., Lu, H., Xue, X., Zhou, Z. (2007). Local Dual Closed Loop Model Based Bayesian Face Tracking. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_12
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DOI: https://doi.org/10.1007/978-3-540-77255-2_12
Publisher Name: Springer, Berlin, Heidelberg
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