Abstract
Many methods have been proposed to solve the problem of shape matching, where the task is to determine similarity between given shapes. In this paper, we propose a novel method to combine many shape matching methods using procedural knowledge to increase the precision of the shape matching process in retrieval problems like place recognition task. The idea of our approach is to assign the best matching method to each template shape providing the best classification for this template. The new incoming shape is compared against all templates using their assigned method. The proposed method increases the accuracy of the classification and decreases the time complexity in comparison to generic classifier combination methods.
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Acknowledgement
This work has been supported by the Czech Science Foundation under research project No. 13-30155P and by the Technology Agency of the Czech Republic under the project no. TE01020197 “Centre for Applied Cybernetics”. The experiments have been run using Grid Infrastructure Metacentrum (project No. LM2010005).
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Košnar, K., Vonásek, V., Kulich, M., Přeučil, L. (2015). Combining Multiple Shape Matching Techniques with Application to Place Recognition Task . In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9008. Springer, Cham. https://doi.org/10.1007/978-3-319-16628-5_29
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DOI: https://doi.org/10.1007/978-3-319-16628-5_29
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