BUDÍKOVÁ, Petra, Jan SEDMIDUBSKÝ, Ján HORVÁTH and Pavel ZEZULA. Towards Scalable Retrieval of Human Motion Episodes. In 22nd IEEE International Symposium on Multimedia (ISM). Washington, DC: IEEE Computer Society. p. 49-56. ISBN 978-1-7281-8697-9. doi:10.1109/ISM.2020.00015. 2020.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Towards Scalable Retrieval of Human Motion Episodes
Authors BUDÍKOVÁ, Petra (203 Czech Republic, belonging to the institution), Jan SEDMIDUBSKÝ (203 Czech Republic, belonging to the institution), Ján HORVÁTH (703 Slovakia, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Washington, DC, 22nd IEEE International Symposium on Multimedia (ISM), p. 49-56, 8 pp. 2020.
Publisher IEEE Computer Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10200 1.2 Computer and information sciences
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14330/20:00114354
Organization unit Faculty of Informatics
ISBN 978-1-7281-8697-9
Doi http://dx.doi.org/10.1109/ISM.2020.00015
UT WoS 000654273000009
Keywords in English skeleton data; human motion retrieval; motion episodes; text-based processing
Tags DISA, firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Petra Budíková, Ph.D., učo 66445. Changed: 16/4/2021 23:02.
Abstract
With the increasing availability of human motion data captured in the form of 2D/3D skeleton sequences, more complex motion recordings need to be processed. In this paper, we study the problem of similarity-based matching of medium-sized unsegmented skeleton sequences, which we denote as motion episodes. We first apply standard pose-based approaches for matching episodes and analyze their shortcomings. Then, we adopt a recent segment-based approach that transforms episode data into a text-like representation, and apply mature text-processing techniques for matching episodes. We demonstrate that this text-based approach achieves promising results in the terms of both effectiveness and efficiency, and can be further indexed to implement scalable episode retrieval.
Links
GA19-02033S, research and development projectName: Vyhledávání, analytika a anotace datových toků lidských pohybů
Investor: Czech Science Foundation
PrintDisplayed: 28/3/2024 19:35