Name
Abstract | ||
|---|---|---|
In this paper we present a combined approach for object localization and classification. Our contribution is twofold. (a) A contextual combination of localization and classification which shows that classification can improve detection and vice versa. (b) An efficient two stage sliding window object localization method that combines the efficiency of a linear classifier with the robustness of a sophisticated non-linear one. Experimental results evaluate the parameters of our two stage sliding window approach and show that our combined object localization and classification methods outperform the state-of-the-art on the PASCAL VOC 2007 and 2008 datasets. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICCV.2009.5459257 | ICCV |
Keywords | DocType | Volume |
pascal voc 2008 datasets,image classification,object localization method,object detection,linear classifier,pascal voc 2007 datasets,two stage sliding window approach,computer vision,detectors,support vector machines,shape,sliding window,kernel | Conference | 2009 |
Issue | ISSN | ISBN |
1 | 1550-5499 E-ISBN : 978-1-4244-4419-9 | 978-1-4244-4419-9 |
Citations | PageRank | References |
81 | 10.11 | 23 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hedi Harzallah | 1 | 315 | 24.79 |
| Frédéric Jurie | 2 | 3924 | 235.82 |
| Cordelia Schmid | 3 | 28581 | 1983.22 |