DocumentCode :
3559608
Title :
Real-time face-priority auto focus for digital and cell-phone cameras
Author :
Rahman, Mohammad T. ; Kehtarnavaz, Nasser
Author_Institution :
Dept. of Electr. Eng., Univ. of Texas at Dallas, Richardson, TX
Volume :
54
Issue :
4
fYear :
2008
fDate :
11/1/2008 12:00:00 AM
Firstpage :
1506
Lastpage :
1513
Abstract :
Auto-focus (AF) has been a key feature in consumer level digital and cell-phone cameras allowing users to focus automatically on a particular plane in a scene in order to get a sharp image. Face priority AF has become of interest lately due to the fact that most pictures captured by consumers are of human faces. In face-priority AF, the focusing decision is made based on a detected face area in the image, thus capturing a sharp picture of the face. While many face detection algorithms exist in the literature, very few of them are actually suitable for real-time software deployment on resource limited digital or cell-phone camera processors. In this paper, a fast face-detection algorithm is introduced by combining a skin color model cluster with a computationally efficient shape processing scheme. Comparison results with a standard algorithm in terms of robustness, speed and accuracy are provided. This face detection algorithm is incorporated into our previously developed rule-based AF method to achieve real-time face-priority AF on an actual digital camera platform.
Keywords :
cameras; face recognition; mobile handsets; shape recognition; cellphone cameras; digital cameras; face detection; face-priority auto focus; shape processing; skin color model cluster; Clustering algorithms; Color; Digital cameras; Face detection; Focusing; Humans; Layout; Shape; Skin; Software algorithms; Face-priority auto focus; cell-phone cameras; digital cameras; real-time face detection;
fLanguage :
English
Journal_Title :
Consumer Electronics, IEEE Transactions on
Publisher :
ieee
Conference_Location :
11/1/2008 12:00:00 AM
ISSN :
0098-3063
Type :
jour
DOI :
10.1109/TCE.2008.4711194
Filename :
4711194
Link To Document :
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