| Home | << 1 >> |
|
| Record | |||||
|---|---|---|---|---|---|
| Author | Monica Piñol; Angel Sappa; Ricardo Toledo | ||||
| Title | MultiTable Reinforcement for Visual Object Recognition | Type | Conference Article | ||
| Year | 2012 | Publication | 4th International Conference on Signal and Image Processing | Abbreviated Journal | |
| Volume | 221 | Issue | Pages | 469-480 | |
| Keywords | |||||
| Abstract | This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach. | ||||
| Address | Coimbatore, India | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer India | Place of Publication | Editor | ||
| Language | Summary Language  |
Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1876-1100 | ISBN | 978-81-322-0996-6 | Medium | |
| Area | Expedition | Conference | ICSIP | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ PST2012 | Serial | 2157 | ||
| Permanent link to this record | |||||