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@inproceedings{1305714, author = {Eliáš, Petr and Sedmidubský, Jan and Zezula, Pavel}, address = {Switzerland}, booktitle = {Proceedings of 8th International Conference on Similarity Search and Applications (SISAP 2015), LNCS 9371}, doi = {http://dx.doi.org/10.1007/978-3-319-25087-8_24}, editor = {G. Amato et al.}, keywords = {motion capture data; motion similarity; visualization; motion image; action classification}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Switzerland}, isbn = {978-3-319-25086-1}, pages = {250-255}, publisher = {Springer}, title = {Motion Images: An Effective Representation of Motion Capture Data for Similarity Search}, year = {2015} }
TY - JOUR ID - 1305714 AU - Eliáš, Petr - Sedmidubský, Jan - Zezula, Pavel PY - 2015 TI - Motion Images: An Effective Representation of Motion Capture Data for Similarity Search PB - Springer CY - Switzerland SN - 9783319250861 KW - motion capture data KW - motion similarity KW - visualization KW - motion image KW - action classification N2 - The rapid development of motion capturing technologies has caused a massive usage of human motion data in a variety of fields, such as computer animation, gaming industry, medicine, sports and security. These technologies produce large volumes of complex spatio-temporal data which need to be effectively compared on the basis of similarity. In contrast to a traditional way of extracting numerical features, we propose a new idea to transform complex motion data into RGB images and compare them by content-based image retrieval methods. We see transformed RGB images as suitable application-independent features for their ability to preserve key aspects of performed motions. To demonstrate the usability of this idea, we evaluate a preliminary experiment that classifies 1,034 motions into 14 categories with the 87.4% precision. ER -
ELIÁŠ, Petr, Jan SEDMIDUBSKÝ a Pavel ZEZULA. Motion Images: An Effective Representation of Motion Capture Data for Similarity Search. In G. Amato et al. \textit{Proceedings of 8th International Conference on Similarity Search and Applications (SISAP 2015), LNCS 9371}. Switzerland: Springer, 2015, s.~250-255. ISBN~978-3-319-25086-1. Dostupné z: https://dx.doi.org/10.1007/978-3-319-25087-8\_{}24.
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