- University of Amsterdam at THUMOS Challenge 2014
- 14th ECCV, THUMOS Challenge workshop (Zürich)
- Book/source title
- THUMOS Challenge 2014: notebook papers
- Orlando, FL: Center for Research in Computer Vision, University of Central Florida
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
This notebook paper describes our approach for the action classification task of the THUMOS Challenge 2014. We investigate and exploit the action-object relationship by capturing both motion and related objects. As local descriptors we use HOG, HOF and MBH computed along the improved dense trajectories. For video encoding we rely on Fisher vector. In addition, we employ deep net features learned from object attributes to capture action context. All actions are classified with a one-versus-rest linear SVM.
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