Abstract
In this paper, we present a subclass-representation approach that predicts the probability of a social image belonging to one particular class. We explore the co-occurrence of user-contributed tags to find subclasses with a strong connection to the top level class. We then project each image onto the resulting subclass space, generating a subclass representation for the image. The advantage of our tag-based subclasses is that they have a chance of being more visually stable and easier to model than top-level classes. Our contribution is to demonstrate that a simple and inexpensive method for generating sub-class representations has the ability to improve classification results in the case of tag classes that are visually highly heterogenous. The approach is evaluated on a set of 1 million photos with 10 top-level classes, from the dataset released by the ACM Multimedia 2013 Yahoo! Large-scale Flickr-tag Image Classification Grand Challenge. Experiments show that the proposed system delivers sound performance for visually diverse classes compared with methods that directly model top classes.
Original language | English |
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Title of host publication | 2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI) |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-4673-8695-1 |
DOIs | |
Publication status | Published - 30 Jun 2016 |
Event | 2016 14th International Workshop on Content-Based Multimedia Indexing - Bucharest, Romania Duration: 15 Jun 2016 → 17 Jun 2016 http://cbmi2016.upb.ro/ |
Conference
Conference | 2016 14th International Workshop on Content-Based Multimedia Indexing |
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Abbreviated title | CBMI |
Country/Territory | Romania |
City | Bucharest |
Period | 15/06/16 → 17/06/16 |
Internet address |
Keywords
- Visualization
- Training
- Predictive models
- Tagging
- Multimedia communication
- Support vector machines
- Flickr