Segmenting and Recognizing Human Action using Low-level Video Features

Daphna Buchsbaum, Kevin R. Canini, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Dividing observed human behavior into individual, meaningful actions is a critical task for both human learners and computer vision systems. An important question is how much action structure and segmentation information is available in the observed surface level motion and image changes, without any knowledge of human pose or behavior. Here we present a novel approach to jointly segmenting and recognizing videos of human action sequences, using a hierarchical topic model. Video sequences are represented as bags of video words, automatically discovered from local space-time interest points. Our model jointly infers both action identification and action segmentation. Our results are a good fit with human segmentation judgments as well as providing relatively accurate action recognition and localization within the videos.

Original languageEnglish (US)
Title of host publicationExpanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011
EditorsLaura Carlson, Christoph Hoelscher, Thomas F. Shipley
PublisherThe Cognitive Science Society
Pages3162-3167
Number of pages6
ISBN (Electronic)9780976831877
StatePublished - 2011
Externally publishedYes
Event33rd Annual Meeting of the Cognitive Science Society: Expanding the Space of Cognitive Science, CogSci 2011 - Boston, United States
Duration: Jul 20 2011Jul 23 2011

Publication series

NameExpanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011

Conference

Conference33rd Annual Meeting of the Cognitive Science Society: Expanding the Space of Cognitive Science, CogSci 2011
Country/TerritoryUnited States
CityBoston
Period7/20/117/23/11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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