This paper presents a neural network based scheme for human face detection and eye localization in color images under non-constrained scene. A Self-growing Probabilistic Decision-based Neural Network (SPDNN) is used to learn the conditional distribution for each color classes. Pixels of a color image are first classified into facial or non-facial regions, then pixels in the facial region are followed by eye region segmentation. The class of each pixel is determined by using the conditional distribution of the chrominance components of pixels belonging to each class. The paper demonstrates a successful application of SPDNN to face detection and eye localization on a database of 755 images from 151 persons. Regarding the performance, experimental results are elaborated in Section 3. As to the processing speed, the face detection and eye localization processes consume approximately 560 ms on a Pentium-II personal computer.
|Number of pages||10|
|State||Published - 1 Dec 2000|
|Event||10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000) - Sydney, Australia|
Duration: 11 Dec 2000 → 13 Dec 2000
|Conference||10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000)|
|Period||11/12/00 → 13/12/00|