SEDMIDUBSKÝ, Jan and Pavel ZEZULA. A Web Application for Subsequence Matching in 3D Human Motion Data. In 19th IEEE International Symposium on Multimedia. Neuveden: IEEE Computer Society, 2017, p. 372-373. ISBN 978-1-5386-2937-6. Available from: https://dx.doi.org/10.1109/ISM.2017.73.
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Basic information
Original name A Web Application for Subsequence Matching in 3D Human Motion Data
Authors SEDMIDUBSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Neuveden, 19th IEEE International Symposium on Multimedia, p. 372-373, 2 pp. 2017.
Publisher IEEE Computer Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Confidentiality degree is not subject to a state or trade secret
Publication form storage medium (CD, DVD, flash disk)
RIV identification code RIV/00216224:14330/17:00094978
Organization unit Faculty of Informatics
ISBN 978-1-5386-2937-6
Doi http://dx.doi.org/10.1109/ISM.2017.73
UT WoS 000454605200066
Keywords in English motion capture data; subsequence matching; similarity comparison; multi-level segmentation; real-time subsequence search; web demonstration application
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 14/5/2020 15:11.
Abstract
The subsequence-matching operation applied to motion capture data searches in long motion sequences to locate their parts that are similar to a query example. An effective and efficient implementation of such operation is valuable to increase reusability and findability of expensively recorded data in the past. This demonstration paper builds on recent advances in the field of motion-data processing and implements them into a single web application that allows users to discover query-similar subsequences. The proposed application does not require any textual annotations nor explicit knowledge of the data and can deal with spatio-temporal variances of human movements. Efficiency and effectiveness can be verified by searching a 12-hour database of motion sequences in real time.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
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