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Description
  • Analysis of human motion data is an important task in many research fields such as sports, medicine, security, and computer animation. In order to fully exploit motion databases for further processing, effective and efficient retrieval methods are needed. However, such task is difficult primarily due to complex spatio-temporal variances of individual human motions and the rapidly increasing volume of motion data. In this paper, we propose a universal content-based subsequence retrieval algorithm for indexing and searching motion data. The algorithm is able to examine database motions and locate all their sub-motions that are similar to a query motion example. We illustrate the algorithm usability by indexing motion features in form of joint-angle rotations extracted from a real-life 68-minute human motion database. We analyse the algorithm time complexity and evaluate retrieval effectiveness by comparing the search results against user-defined ground truth.
  • Analysis of human motion data is an important task in many research fields such as sports, medicine, security, and computer animation. In order to fully exploit motion databases for further processing, effective and efficient retrieval methods are needed. However, such task is difficult primarily due to complex spatio-temporal variances of individual human motions and the rapidly increasing volume of motion data. In this paper, we propose a universal content-based subsequence retrieval algorithm for indexing and searching motion data. The algorithm is able to examine database motions and locate all their sub-motions that are similar to a query motion example. We illustrate the algorithm usability by indexing motion features in form of joint-angle rotations extracted from a real-life 68-minute human motion database. We analyse the algorithm time complexity and evaluate retrieval effectiveness by comparing the search results against user-defined ground truth. (en)
Title
  • A Key-Pose Similarity Algorithm for Motion Data Retrieval
  • A Key-Pose Similarity Algorithm for Motion Data Retrieval (en)
skos:prefLabel
  • A Key-Pose Similarity Algorithm for Motion Data Retrieval
  • A Key-Pose Similarity Algorithm for Motion Data Retrieval (en)
skos:notation
  • RIV/00216224:14330/13:00065724!RIV14-MV0-14330___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GBP103/12/G084), P(VG20122015073)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 58669
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00065724
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • motion capture data; motion retrieval; subsequence retrieval; similar sub-motions (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [C2477BD56460]
http://linked.open...v/mistoKonaniAkce
  • Poznan, Poland
http://linked.open...i/riv/mistoVydani
  • Switzerland
http://linked.open...i/riv/nazevZdroje
  • Proceedings of 12th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2013), LNCS 8192
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Sedmidubský, Jan
  • Zezula, Pavel
  • Valčík, Jakub
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-319-02895-8_60
http://purl.org/ne...btex#hasPublisher
  • Springer International Publishing
https://schema.org/isbn
  • 9783319028941
http://localhost/t...ganizacniJednotka
  • 14330
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