Abstract
Bag-of-words (BoW) is one of the most successful methods for object categorization. This paper proposes a statistical codeword selection algorithm where the best subset is selected from the initial codewords based on the statistical characteristics of codewords. For this purpose, we defined two types of codeword-confidences: cross- and within-category confidences. The cross- and within-category confidences eliminate indistinctive codewords across categories and inconsistent codewords within each category, respectively. An informative subset of codewords is then selected based on these two codeword-confidences. The experimental evaluation for a scene categorization dataset and a Caltech-101 dataset shows that the proposed method improves the categorization performance up to 10% in terms of error rate reduction when cooperated with BoW, sparse coding (SC), and locality-constrained liner coding (LLC). Furthermore, the codeword size is reduced by 50% leading a low computational complexity.
Original language | English |
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Title of host publication | Proceedings of SPIE-IS and T Electronic Imaging - Intelligent Robots and Computer Vision XXXII |
Subtitle of host publication | Algorithms and Techniques |
Editors | Juha Roning, David Casasent |
Publisher | SPIE |
ISBN (Electronic) | 9781628414967 |
DOIs | |
Publication status | Published - 2015 |
Event | Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques - San Francisco, United States Duration: 2015 Feb 9 → 2015 Feb 10 |
Publication series
Name | Proceedings of SPIE - The International Society for Optical Engineering |
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Volume | 9406 |
ISSN (Print) | 0277-786X |
ISSN (Electronic) | 1996-756X |
Other
Other | Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques |
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Country | United States |
City | San Francisco |
Period | 15/2/9 → 15/2/10 |
Bibliographical note
Publisher Copyright:© 2015 SPIE-IS&T.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering