Efficient Indexing of 3D Human Motions

BUDÍKOVÁ, Petra, Jan SEDMIDUBSKÝ and Pavel ZEZULA. Efficient Indexing of 3D Human Motions. Online. In ACM International Conference on Multimedia Retrieval (ICMR). Neuveden: ACM, 2021, p. 10-18. ISBN 978-1-4503-8463-6. Available from: https://dx.doi.org/10.1145/3460426.3463646.

Basic information

• Original name: Efficient Indexing of 3D Human Motions
• Authors: BUDÍKOVÁ, Petra (203 Czech Republic, guarantor, belonging to the institution), Jan SEDMIDUBSKÝ (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
• Edition: Neuveden, ACM International Conference on Multimedia Retrieval (ICMR), p. 10-18, 9 pp. 2021.
• Publisher: ACM

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
• WWW: URL
• RIV identification code: RIV/00216224:14330/21:00118943
• Organization unit: Faculty of Informatics
• ISBN: 978-1-4503-8463-6
• Doi: http://dx.doi.org/10.1145/3460426.3463646
• UT WoS: 000723651900002
• Keywords in English: human motion data; skeleton sequences; motion word; text-based processing; indexing; extended inverted files; ranked retrieval; approximate searching; scalability
• Tags: DISA, firank_A
• Tags: International impact, Reviewed

Abstract

Digitization of human motion using 2D or 3D skeleton representations offers exciting possibilities for many applications but, at the same time, requires scalable content-based retrieval techniques to make such data reusable. Although a lot of research effort focuses on extracting content-preserving motion features, there is a lack of techniques that support efficient similarity search on a large scale. In this paper, we introduce a new indexing scheme for organizing large collections of spatio-temporal skeleton sequences. Specifically, we apply the motion-word concept to transform skeleton sequences into structured text-like motion documents, and index such documents using an extended inverted-file approach. Over this index, we design a new similarity search algorithm that exploits the properties of the motion-word representation and provides efficient retrieval with a variable level of approximation, possibly reaching constant search costs disregarding the collection size. Experimental results confirm the usefulness of the proposed approach.

Links

• GA19-02033S, research and development project: Name: Vyhledávání, analytika a anotace datových toků lidských pohybů

Investor: Czech Science Foundation