Using Skin Color and HAD-AdaBoost Algorithm for Face Detection in Color Images
Li-Jie Xue, Zheng-Ming Li
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.76How to use a DOI?
- face detection; skin color segmentation; AD AdaBoost; heuristics-structured cascade
- Owing to the interference of the complex background in color image, high false positive rate is a problem in face detection based on AdaBoost algorithm. In addition, the training process of AdaBoost is very time consuming. To address these problems, this paper proposes a two-stage face detection method using skin color segmentation and heuristics-structured adaptive to detection AdaBoost (HAD-AdaBoost) algorithm. Firstly, skin color segmentation is applied to remove most of the background. Then, the HAD-AdaBoost cascade classifier is performed on the candidates to make a final face location. By introducing the algorithm of adaptive to detection AdaBoost algorithm (AD AdaBoost) and heuristicsstructured cascade to our system, the resulting classifier consisting of fewer weak classifiers achieves lower error rates. The experimental results demonstrate that our system retrieves 90.24% of the detection rate with 1.69% false alarms on the color image set.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Li-Jie Xue AU - Zheng-Ming Li PY - 2012/11 DA - 2012/11 TI - Using Skin Color and HAD-AdaBoost Algorithm for Face Detection in Color Images BT - 2012 National Conference on Information Technology and Computer Science PB - Atlantis Press SP - 288 EP - 291 SN - 1951-6851 UR - https://doi.org/10.2991/citcs.2012.76 DO - https://doi.org/10.2991/citcs.2012.76 ID - Xue2012/11 ER -