Abstract:
In order to improve the detection speed and decrease the false alarm rate of the AdaBoost algorithm in high resolution color image, a multi-feature fusion method is proposed. It adopts cascade strategy to combine multi-fuse classifiers. Benefiting from the complementary of multi-feature, the proposed method can achieve high performance. Experimental result demonstrates that the proposed method has better global precision and is less time consuming.
Key words:
face detection,
cascade structure,
feature classifier
摘要:
针对AdaBoost人脸检测方法在高分辨率彩色图像上定位速度慢和误检率高的问题,提出一种多特征融合的人脸检测方法。该方法使用级联策略将多种特征分类器有效地组合起来,高效地利用各种特征之间的互补性,形成一种新型的高性能分类器。实验结果显示,该方法提高了检测速度、降低了误检率。
关键词:
人脸检测,
级联结构,
特征分类器
CLC Number:
LU Feng- Chen-Yi-Song- Chen-Wen-An. Cascade Based Multi-feature Fusion MethodAlgorithm for Face Detection[J]. Computer Engineering, 2011, 37(2): 7-9.
鲁鹏 陈毅松 陈文广. 基于级联框架下的多特征融合人脸检测算法[J]. 计算机工程, 2011, 37(2): 7-9.