An algorithm of static human face detection based on BP network is proposed.
提出了一种基于BP神经网络的静态人脸检测算法。
Human face detection is one of the most important research fields on pattern recognition.
人脸的检测、识别是当前模式识别中重要的研究方向。
An approach based on KL transform and Mosaic image model for human face detection is proposed.
提出了一种基于KL变换和镶嵌图模型的人脸检测方法。
Finally, it studies the application of the edge detection in human face detection and recognition.
最后通过实例研究了人脸边缘检测在人脸检测和识别中的具体应用。
Based on facial features extraction and verification, we present a new human face detection method.
提出了一种基于特征提取和验证相结合的人脸检测方法。
Due to its complexity, it is difficult to describe the rules of human face detection and recognition.
人脸的检测和识别是一个非常复杂的问题，对它的许多规律和规则进行显性的描述是相当困难的。
For the function of autonomous patrol, we have designed the human face detection and smile recognition algorithm.
为了实现机器人自主巡逻功能，本文设计了人脸检测与笑脸识别算法。
In this paper, a human face detection method based on skin color model and structural features of face is presented.
本文提出了基于人脸肤色模型和人脸结构特征的人脸检测。
In this paper, a fast human face detection method based on difference image and multi-templates 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。
A human face detection method based on coarse segmentation of difference image and multi-template matching is proposed.
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 complete Human Face Recognition System should include Human Face Detection, Feature Extraction, and Match Recognition.
一个完整的人脸识别系统包括人脸检测、特征提取、以及匹配识别。
The result of the experiment shows that this approach can solve the problem of multi human face detection from complex scene.
实验结果表明，该方法能够较好地解决复杂背景下的正面人脸的检测问题。
This paper studies the human face detection by support vector classifier using histograms of color, color edge and its orientation.
研究了利用颜色直方图、颜色边缘幅值和边缘方向直方图特征，基于支撑向量分类器的检测人脸技术。
In this paper, we provide a new human face detection algorithm based on template-matching, Mosaic image and Support Vector Machines.
本文提出了一种基于模板匹配、马赛克图和支持向量机的人脸检测算法。
A method for human face detection under complex background is proposed on the basis of human vision mechanism and skin color clustering features.
在人类视觉机制和肤色聚类特性的基础上，提出了一种复杂背景下人脸检测方法。
This paper presents a human face detection and localization approach which is based on skin color detection and principle component analysis (PCA).
提出一种基于人脸肤色统计模型和主元分析(pca)的人脸检测和定位方法。
This paper proposes a new method of detecting and tracking video-based human faces, which includes the aspects of human face detection and object tracking.
本文提出了一种视频人脸的定位与跟踪算法，包括人脸检测和人脸跟踪两个方面。
Human face problems consist of four parts: human face detection, human face tracking, identification of human face and the interrelated pose and expression.
人脸问题主要包括：人脸检测、人脸跟踪、人脸识别，以及其衍生出来的姿态和表情分析四个应用领域。
Human face problems consist of four parts: human face detection, human face tracking, human face recognition and the derived analysis of pose and expression.
人脸问题主要包括：人脸检测、人脸跟踪、人脸识别，以及其衍生出来的姿态和表情分析四个应用领域。
This part briefly introduces the concepts of human face detection and SVM, analyzes common face detection methods and how SVM be applied to learning and classifying.
文章简要介绍了人脸检测和支持向量机的概念，重点分析了常用的人脸检测方法和支持向量机如何应用于学习分类。
Human face automatic recognition system is a cross subject combined with pattern recognition, computer vision and biometrics, in which human face detection is a key factor.
人脸识别是模式识别与计算机视觉、生物识别技术的交叉学科，而人脸检测是人脸识别系统的关键环节。
The feature of skin color is an important feature of human being, which plays a key role in human face detection and recognition, objectionable image filtering based on content, etc.
肤色特征是人体表面的重要特征，在人脸检测与识别、基于内容的不良图像过滤系统中有着重要的地位。
At the same time, since the human face detection can be greatly influenced by background, light, gesture, expression, occlusion, noise and so on, it also became a much complicated topic.
同时，由于人脸检测受背景、光照、姿态、表情、遮挡、噪声等影响较大，也成为一个较为复杂的课题。
A novel human face detection method is introduced, which is based on chrominance colour information feature from an image containing one face in indoor environment with non-uniform background.
介绍了一种新颖的人脸检测方法，该方法基于非统一背景下室内环境中单幅人脸图像的色度特征信息。
This paper mainly make research on classify methods based on statistical theory, support vector machine (SVM), and feature extraction method-wavelet transform, and using them in human face detection.
本文主要研究目前较为流行的基于统计学习理论的分类方法——支持向量机方法(SVM)，以及小波变换提取特征的方法，将其用于人脸检测。
After comparing and analyzing existing face detection methods based on complexion, a skin model used to detect human faces in this thesis, Gaussian distribution model is proposed.
研究了常见的基于肤色的人脸检测算法并分析比较其优缺点，给出本文利用肤色特征进行肤色检测时所采用的肤色模型——高斯分布模型。
Head and shoulder detection is one of the important problems on human body analysis. It is the first step of face detection and the base of pedestrian detection.
头肩图像检测是人体分析研究中受关注的研究方向，是人脸检测的第一步，也是行人检测的基础。
According to analysing the human face and converting face detection in complex background into facial detection, a face detection model is built with facial feature being detective feature.
基于面向人脸的分析，按照将复杂背景中的人脸检测转化为对五官检测的思想，建立了以五官结构为检测特征的人脸检测模型。
Face detection find faces information in the video sequence or image and determine facial size, position, trajectory, attitude, and further human face eyes, lips and other features extraction process.
人脸检测是指在视频序列或图像中寻找所有人脸信息，并确定人脸大小、位置、运动轨迹、姿态，进一步对人脸上的眼睛、嘴唇等特征进行提取的过程。
Face detection find faces information in the video sequence or image and determine facial size, position, trajectory, attitude, and further human face eyes, lips and other features extraction process.
人脸检测是指在视频序列或图像中寻找所有人脸信息，并确定人脸大小、位置、运动轨迹、姿态，进一步对人脸上的眼睛、嘴唇等特征进行提取的过程。
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