DocumentCode
3136634
Title
Unsupervised clustering for google searches of celebrity images
Author
Holub, Alex ; Moreels, Pierre ; Perona, Pietro
Author_Institution
California Inst. of Technol., Pasadena, CA
fYear
2008
fDate
17-19 Sept. 2008
Firstpage
1
Lastpage
8
Abstract
How do we identify images of the same person in photo albums? How can we find images of a particular celebrity using Web image search engines? These types of tasks require solving numerous challenging issues in computer vision including: detecting whether an image contains a face, maintaining robustness to lighting, pose, occlusion, scale, and image quality, and using appropriate distance metrics to identify and compare different faces. In this paper we present a complete system which yields good performance on challenging tasks involving face recognition including image retrieval, unsupervised clustering of faces, and increasing precision of dasiaGoogle Imagepsila searches. All tasks use highly variable real data obtained from raw image searches on the web.
Keywords
Internet; computer vision; face recognition; hidden feature removal; image retrieval; object detection; pattern clustering; pose estimation; search engines; unsupervised learning; Google search engine; Web image retrieval; celebrity image detection; computer vision; distance metrics; face recognition; image quality; occlusion method; pose estimation; unsupervised clustering; Computer vision; Eyebrows; Eyes; Face detection; Face recognition; Image quality; Mouth; Nose; Robustness; Search engines;
fLanguage
English
Publisher
ieee
Conference_Titel
Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on
Conference_Location
Amsterdam
Print_ISBN
978-1-4244-2153-4
Electronic_ISBN
978-1-4244-2154-1
Type
conf
DOI
10.1109/AFGR.2008.4813463
Filename
4813463
Link To Document