DocumentCode :
2289590
Title :
Combining efficient object localization and image classification
Author :
Harzallah, Hedi ; Jurie, Frédéric ; Schmid, Cordelia
Author_Institution :
LEAR, INRIA Grenoble, Grenoble, France
fYear :
2009
fDate :
Sept. 29 2009-Oct. 2 2009
Firstpage :
237
Lastpage :
244
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.
Keywords :
image classification; object detection; PASCAL VOC 2007 datasets; PASCAL VOC 2008 datasets; image classification; linear classifier; object localization method; two stage sliding window approach; Detectors; Image classification; Image segmentation; Layout; Machine learning; Machine learning algorithms; Object detection; Robustness; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
ISSN :
1550-5499
Print_ISBN :
978-1-4244-4420-5
Electronic_ISBN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2009.5459257
Filename :
5459257
Link To Document :
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