Title :
A real-time face tracker for color video
Author :
Spors, S. ; Rabenstein, R.
Author_Institution :
Telecommun. Lab., Erlangen-Nurnberg Univ., Erlangen, Germany
Abstract :
This paper presents a face localization and tracking algorithm which is based upon skin color detection and principal component analysis (PCA) based eye localization. Skin color segmentation is performed using statistical models for human skin color. The skin color segmentation task results in a mask marking the skin color regions in the actual frame, which is further used to compute the position and size of the dominant facial region utilizing a robust statistics-based localization method. To improve the results of skin color segmentation, a foreground/background segmentation and an adaptive background update scheme are added. Additionally, the derived face position is tracked with a Kalman filter. To overcome the problem of skin color ambiguity, an eye detection algorithm based on PCA is presented
Keywords :
Kalman filters; face recognition; feature extraction; image colour analysis; image motion analysis; image segmentation; principal component analysis; skin; video signal processing; Kalman filter; PCA; color video; eye detection; face localization; object motion model; principal component analysis; real-time face tracking; skin color detection; skin color segmentation; statistical models; Algorithm design and analysis; Face detection; Humans; Image analysis; Image color analysis; Image segmentation; Pixel; Principal component analysis; Robustness; Skin;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7803-7041-4
DOI :
10.1109/ICASSP.2001.941214