Abstract
We propose a new method to detect human faces in color images. A human skin color model is built to capture the chromatic properties based on multivariate statistical analysis. Given a color image, multiscale segmentation is used to generate homogeneous regions at multiple different scales. From the coarsest to the finest scale, regions of skin color are merged until the shape is approximately elliptic. Postprocessing is performed to determine whether a merged region contains a human face and include the facial features of non-skin color such as eyes and mouth if necessary. Experimental results show that human faces in color images can be detected regardless of size, orientation and viewpoint.
| Original language | English |
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| Pages | 127-130 |
| Number of pages | 4 |
| Publication status | Published - 1998 |
| Event | Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA Duration: 1998 Oct 4 → 1998 Oct 7 |
Other
| Other | Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) |
|---|---|
| City | Chicago, IL, USA |
| Period | 98/10/4 → 98/10/7 |
Bibliographical note
Funding Information:The authors would like to thank David Kriegman and Peter Belhumeur of Yale University and Bernard Achermann of the University of Bern for making their face databases available to them. The support of the National Science Foundation under grant IRI-9529045 is also greatly appreciated.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering