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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 and 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, p.~250-255. ISBN~978-3-319-25086-1. Available from: https://dx.doi.org/10.1007/978-3-319-25087-8\_{}24.
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