DocumentCode
2652200
Title
Iterative unsupervised object detection system
Author
Onis, S. ; Sanson, H. ; Garcia, C.
Author_Institution
Orange Labs., Rennes
fYear
2008
fDate
25-28 June 2008
Firstpage
397
Lastpage
400
Abstract
Current object detection systems provide good results, at the expense of requiring a large training database. This paper presents an unsupervised iterative object detection system using a selection of previously detected objects in order to perform new object detection. Our experiments show that this method enables face detection with a greatly reduced set of examples and outperforms the detection rates of our non iterative detection system based on normalized cross-correlation and affine deformation compensation.
Keywords
face recognition; iterative methods; object detection; affine deformation compensation; detection rates; face detection; iterative unsupervised object detection system; Computer vision; Detectors; Face detection; Image databases; Iterative methods; Motion segmentation; Neural networks; Object detection; Performance evaluation; System testing; affine deformation; correlation; detection; iterative; unsupervised;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing, 2008. IWSSIP 2008. 15th International Conference on
Conference_Location
Bratislava
Print_ISBN
978-80-227-2856-0
Electronic_ISBN
978-80-227-2880-5
Type
conf
DOI
10.1109/IWSSIP.2008.4604450
Filename
4604450
Link To Document