- Real-time bag of words, approximately
- ACM International Conference on Image and Video Retrieval (ACM-CIVR 2009), Santorini Island, Greece
- Book/source title
- Proceedings of the ACM International Conference on Image and Video Retrieval, ACM-CIVR 2009: July 8-10, 2009 - Santorini Island, Greece
- Pages (from-to)
- New York: Association for Computing Machinery (ACM)
- Document type
- Conference contribution
- Interfacultary Research Institutes
Faculty of Science (FNWI)
- Institute for Logic, Language and Computation (ILLC)
Informatics Institute (IVI)
We start from the state-of-the-art Bag of Words pipeline that in the 2008 benchmarks of TRECvid and PASCAL yielded the best performance scores. We have contributed to that pipeline, which now forms the basis to compare various fast alternatives for all of its components: (i) For descriptor extraction we propose a fast algorithm to densely sample SIFT and SURF, and we compare several variants of these descriptors. (ii) For descriptor projection we compare a k-means visual vocabulary with a Random Forest. As a preprojection step we experiment with PCA on the descriptors to decrease projection time. (iii) For classification we use Support Vector Machines and compare the x2 kernel with the RBF kernel. Our results lead to a 10-fold speed increase without any loss of accuracy and to a 30-fold speed increase with 17% loss of accuracy, where the latter system does real-time classification at 26 images per second.
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