Abstract
In this work, we present a C++ implementation of object categorization with the bag-of-word (BoW) framework. Unlike typical BoW models which consider the whole area of an image as the region of interest (ROI) for visual codebook generation, our implementation only considers the regions of target objects as ROIs and the unrelated backgrounds will be excluded for generating codebook. This is achieved by a supervised mean shift algorithm. Our work is on the benchmark SIVAL dataset and utilizes a Maximum Margin Supervised Topic Model for classification. The final performance of our work is quite encouraging.
Original language | English |
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Title of host publication | Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings |
Publisher | Springer Verlag |
Pages | 611-614 |
Number of pages | 4 |
Edition | PART 3 |
ISBN (Print) | 9783642338847 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings - Florence, Italy Duration: 7 Oct 2012 → 13 Oct 2012 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Number | PART 3 |
Volume | 7585 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings |
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Country/Territory | Italy |
City | Florence |
Period | 7/10/12 → 13/10/12 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science
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Du, R., Wu, Q., He, X., & Yang, J. (2012). Object categorization based on a supervised mean shift algorithm. In Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings (PART 3 ed., pp. 611-614). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7585 LNCS, No. PART 3). Springer Verlag. https://doi.org/10.1007/978-3-642-33885-4_64