Title :
Iterative unsupervised object detection system
Author :
Onis, S. ; Sanson, H. ; Garcia, C.
Author_Institution :
Orange Labs., Rennes
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;
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
DOI :
10.1109/IWSSIP.2008.4604450
