About: Semantically Consistent Human Motion Segmentation     Goto   Sponge   NotDistinct   Permalink

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Description
  • The development of motion capturing devices like Microsoft Kinect poses new challenges in the exploitation of human-motion data for various application fields, such as computer animation, visual surveillance, sports or physical medicine. In such applications, motion segmentation is recognized as one of the most fundamental steps. Existing methods usually segment motions at the level of logical actions, like walking or jumping, to annotate the motion segments by textual descriptions. Although the action-level segmentation is convenient for motion summarization and action retrieval, it does not suit for general action-independent motion retrieval. In this paper, we introduce a novel semantically consistent algorithm for partitioning motions into short and further non-divisible segments. The property of semantic consistency ensures that the start and end of each segment are detected at semantically equivalent phases of movement to support general motion retrieval.
  • The development of motion capturing devices like Microsoft Kinect poses new challenges in the exploitation of human-motion data for various application fields, such as computer animation, visual surveillance, sports or physical medicine. In such applications, motion segmentation is recognized as one of the most fundamental steps. Existing methods usually segment motions at the level of logical actions, like walking or jumping, to annotate the motion segments by textual descriptions. Although the action-level segmentation is convenient for motion summarization and action retrieval, it does not suit for general action-independent motion retrieval. In this paper, we introduce a novel semantically consistent algorithm for partitioning motions into short and further non-divisible segments. The property of semantic consistency ensures that the start and end of each segment are detected at semantically equivalent phases of movement to support general motion retrieval. (en)
Title
  • Semantically Consistent Human Motion Segmentation
  • Semantically Consistent Human Motion Segmentation (en)
skos:prefLabel
  • Semantically Consistent Human Motion Segmentation
  • Semantically Consistent Human Motion Segmentation (en)
skos:notation
  • RIV/00216224:14330/14:00073223!RIV15-MV0-14330___
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
  • 44384
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/14:00073223
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • motion capture data; segmentation; semantic consistency; phases of movement; motion retrieval (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [3D6185BC4593]
http://linked.open...v/mistoKonaniAkce
  • Munich, Germany
http://linked.open...i/riv/mistoVydani
  • Switzerland
http://linked.open...i/riv/nazevZdroje
  • Proceedings of 25th International Conference on Database and Expert Systems Applications (DEXA 2014), LNCS 8644
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
  • Balážia, Michal
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-319-10073-9_36
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 9783319100722
http://localhost/t...ganizacniJednotka
  • 14330
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