提出了基于差影法粗分割与多模板匹配的人脸检测方法。
A human face detection method based on coarse segmentation of difference image and multi-template matching is proposed.
提出了一种用差影法与多模板匹配快速实现人脸检测的方法。
In this paper, a fast human face detection method based on difference image and multi-templates matching is proposed.
提出了一种基于多模板匹配的一般环境图象中单人脸的检测方法。
This paper develops a multi template matching based method for single face detection in general background images.
提出一种用于说话人识别的方法基于特征空间轨迹的多模板匹配法。
This paper presents a multiple templets matching algorithm based on feature space trace, which is used in speaker recognition.
针对一种基于多模板匹配的单人脸检测方法的不足，提出了一种改进的人脸检测方法。
Taking into account of the weakness of a single face detection method based on multiple templates matching, an improved face detection method is presented.
这种算法大大减小了搜索人脸的范围，使得检测速度比单纯仅用多模板匹配来检测人脸提高了三倍多。
The algorithm reduces the range where faces are to be searched, therefore its detection speed is three times of that of other detection methods used singly by multi-template matching.
图像与模板的相关值是一多峰值函数，模板匹配实质上是多峰值寻优过程。
The correlation value of an image and its template was a multimodal function, so template matching can be seen as.
首先利用模板匹配进行粗分类，将多类问题转化成两类问题，再利用支持向量机进行精确分类。
In the proposed method, the original problem is firstly question firstly coarsely classified into a two-classes problem by using template matching, and then are accurately classified by means of SVM.
首先利用模板匹配进行粗分类，将多类问题转化成两类问题，再利用支持向量机进行精确分类。
In the proposed method, the original problem is firstly question firstly coarsely classified into a two-classes problem by using template matching, and then are accurately classified by means of SVM.
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