Abstract
This work develops a novel and robust hierarchical search tree matching algorithm, in which the Distance Transform based pedestrian silhouette template database is constructed for efficient pedestrian identification. The proposed algorithm was implemented and its performance assessed. The proposed method achieved an accuracy of 89% true positive, 92% true negative and low false positive 8% rates when matching 1069 pedestrian objects and 568 non-pedestrian objects. The contributions of this work are twofold. First, a novel pedestrian silhouette database is presented based on the Chamfer Distance Transform. Second, the proposed hierarchical search tree matching strategy utilizing Fuzzy C-means clustering method can be adopted for mapping and locating pedestrian objects with robustness and efficiency.
This work was supported in part by the National Science Council, Taiwan, R.O.C. grants NSC96-2221-E-305-008-MY3 and Ministry of Economics grant No. 97EC17A02S1032 Construction of Vision-Based Intelligent Environment (II). Mr. Shun-Chun Lee is also commended for his work in the preliminary study.
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Lin, DT., Liu, LW. (2009). Pedestrian Identification with Distance Transform and Hierarchical Search Tree. In: Velásquez, J.D., RÃos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_54
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DOI: https://doi.org/10.1007/978-3-642-04592-9_54
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