提出一种基于混合肤色模型的实时人脸跟踪方法。
Th paper presents a new real-time face tracking method based on a mixed skin-color model.
提出了一种基于肤色模型与眼睛定位的人脸检测方法。
A method for the face detection based on skin color model and eye location is proposed.
提出了一种使用BP人工神经网络建立的人体肤色模型。
This paper presents a new human skin color model using BP networks.
再利用肤色模型进行肤色分割，将肤色与背景区分开来。
Then distinguish the face area from background area by the complexion module.
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 human face detection method based on skin color model and structural features of face is presented.
SS肤色检测模型，在功能上是色彩空间和肤色模型的结合。
RGB-SS skin detection models, as for the function, is combination of color space and complexion model.
本文提出了一种将光线补偿和肤色模型相结合的人脸检测算法。
This paper promotes a face detection algorithm combining light compensation and skin color model.
利用RGB肤色模型可以很好的分割肤色，这里经试验给定了一定的数值。
RGB color model can be a good use of the division of color, and tested here, given a certain value.
文章提出了一种基于肤色模型，结合椭圆环模板进行人脸跟踪及姿态估计的算法。
This paper presents an algorithm for facial tracking and pose estimation based on skin color model and elliptical template.
目前手势识别系统主要是利用肤色模型分割手部区域，检测结果易受光照、背景等条件影响。
Most gesture recognition systems use skin color model to segment hand. The segmentation results are affected by to the light, background and other conditions.
在常见的RGB颜色空间的上，建立了肤色模型，通过有效的阈值估计方法，实现肤色识别。
Firstly, in common RGB color space, established the skin model, through effective threshold estimation method, realized the skin recognition.
脸部位置的检测定位主要建立肤色模型以及计算肤色相似度图，通过阈值分割方法进行分类和定位。
The method of face detection is establishment of skin color model and computation of similarity graph, then classify by threshold segmentation.
利用人脸检测结果，结合混合高斯模型，以人脸肤色为样本在线建立了具有针对性的人体肤色模型。
Since a human face has the similar skin color distribution with the human body, we can use the skin pixels in a detected face to build the skin color model of human body dynamically by GMM.
首先，根据肤色的聚类特征，在对比分析常用彩色空间特性的基础上建立肤色模型，对人手进行分割。
Firstly, according to the clustering character of skin color, the human hand is segmented via building the skin color model by analyzing the characters of common color Spaces.
以人脸肤色模型为基础，结合目标形状特征识别方法，并用扩展卡尔曼滤波估计目标运动轨迹，实现基于肤色的人脸实时跟踪鲁棒方法。
The face motion could be estimated by using face skin color model integrated with feature based object recognition technique and extended Kalman filter.
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。
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.
在皮肤检测阶段，在总结前人工作的基础上，采用了一种有效的肤色检测模型，并在此基础上利用简单统计纹理特征进行皮肤检测。
In period of skin detection, we adopted an effective skin color model by studying the former work and based on this we carried out skin detection through simple and statistical texture character.
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 presents a human face detection and localization approach which is based on skin color detection and principle component analysis (PCA).
在复杂背景情况下，采用固定的阈值边界模型进行肤色分割将导致较大的漏检或误检。
As a result, for images with complex backgrounds, a fixed decision boundary skin-color model may lead to high false rejection rate and false detection rate.
利用检测过程中人脸区域初始化跟踪窗口，建立肤色的色调信息模型对后续帧进行跟踪。
Firstly, the tracking window based on face region was initialized in detecting process. Then, color hue information model was established to track the follow-up frame.
特征肤色的方法是针对彩色图像的人脸检测方法，针对灰度图像本文采用基于隐马尔可夫模型的人脸识别方法来检测人脸。
The eigen skin-color method is for the color images. For gray images, this paper USES face recognition method based on hidden Markov models to detect human faces.
针对这点，本文提出肤色平滑度的概念，并利用这一概念和HSV颜色模型对图像进行分割。
By this concept and together with HSV color model, we can successfully segment the face image.
由于室内存在多种物体，背景不断变化，且光照条件可能不断变化，提出采用人脸肤色的标准混合高斯模型与人眼特征相结合的人脸检测法，无需对原始图像进行尺度变换。
An effective and fast method of face detection for a service robot is proposed, which combines a mixture of Gaussian distribution model of skin tone color with eyes features.
本文讨论了利用肤色信息进行人脸检测后，采用伪二维隐马尔可夫模型通过训练和识别两个基本部分建立起人脸识别系统。
In this paper we set up a face recognition system based on P2D-HMM with the two steps of drilling and recognizing after the face detection of complexion information.
通过实验比较，最终选择算法简单、正确率高的色度空间模型作为肤色检测模型。
Through the comparing with the experiments, the Chroma Space model was simply and had a good effect, so it was selected as the skin-color detecting model.
本文介绍了常用的三种肤色检测模型：统计颜色模型、色度空间模型和高斯混合模型。
This paper introduced three skin-color detecting model: Statistical color model, Chroma Space model and Gaussian Mixture model.
本文介绍了常用的三种肤色检测模型：统计颜色模型、色度空间模型和高斯混合模型。
This paper introduced three skin-color detecting model: Statistical color model, Chroma Space model and Gaussian Mixture model.
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