Detailed Information on Publication Record
2022
Visual Exploration of Human Motion Data
BUDÍKOVÁ, Petra, Daniel KLEPÁČ, Dávid RUSNÁK and Milan SLOVÁKBasic information
Original name
Visual Exploration of Human Motion Data
Authors
BUDÍKOVÁ, Petra (203 Czech Republic, guarantor, belonging to the institution), Daniel KLEPÁČ (203 Czech Republic, belonging to the institution), Dávid RUSNÁK (703 Slovakia, belonging to the institution) and Milan SLOVÁK (203 Czech Republic, belonging to the institution)
Edition
Neuveden, 15th International Conference on Similarity Search and Applications (SISAP 2022), p. 64-71, 8 pp. 2022
Publisher
Springer, Cham
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10200 1.2 Computer and information sciences
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
References:
Impact factor
Impact factor: 0.402 in 2005
RIV identification code
RIV/00216224:14330/22:00128918
Organization unit
Faculty of Informatics
ISBN
978-3-031-17848-1
ISSN
UT WoS
000874756300006
Keywords in English
Human motion data; Skeleton sequences; Visualization; Multimedia exploration; Explainability of similarity
Tags
International impact, Reviewed
Změněno: 28/3/2023 12:47, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
Human motion data are beginning to appear in many application domains, which brings a need to develop user-friendly motion processing applications. One of important open challenges is the presentation of high-dimensional spatio-temporal motion data to end users in a way that is easy to understand and allows fast browsing and exploration of the motion datasets. For many applications such as computer-assisted rehabilitation or motion learning, it is also very desirable to visualize the differences between two motion sequences. In this paper, we present a publicly available software tool that provides the visualization functionality for individual motion sequences, comparison of two motions, and exploration of large motion datasets.