This paper presents a new human skin color model using BP networks.
提出了一种使用BP人工神经网络建立的人体肤色模型。
In the new color space, the skin color model is established using Gaussian model.
在新的彩色空间中，用高斯模型来建立皮肤模型。
A method for the face detection based on skin color model and eye location is proposed.
提出了一种基于肤色模型与眼睛定位的人脸检测方法。
This paper promotes a face detection algorithm combining light compensation and skin color 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。
Hand area is segmented based on skin color model, then the hand contour is described by use of Fourier descriptor.
基于皮肤颜色模型进行手势分割，并用傅里叶描述子描述轮廓。
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。
This paper presents an algorithm for facial tracking and pose estimation based on skin color model and elliptical template.
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。
The method of face detection is establishment of skin color model and computation of similarity graph, then classify by threshold segmentation.
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 face motion could be estimated by using face skin color model integrated with feature based object recognition technique and extended Kalman filter.
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。
Most gesture recognition systems use skin color model to segment hand. The segmentation results are affected by to the light, background and other conditions.
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。
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.
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。
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.
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。
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.
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。
An introduction of RGB color model and YUV color model, the particular analysis of skin color in photo use YUV color model.
简单介绍RGB彩色模型与YUV彩色模型，以及面部照片中皮肤颜色在YUV彩色空间中的详细分析。
RGB-SS skin detection models, as for the function, is combination of color space and complexion model.
SS肤色检测模型，在功能上是色彩空间和肤色模型的结合。
Firstly, in common RGB color space, established the skin model, through effective threshold estimation method, realized the skin recognition.
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。
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。
Th paper presents a new real-time face tracking method based on a mixed skin-color model.
提出一种基于混合肤色模型的实时人脸跟踪方法。
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.
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。
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.
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。
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.
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.
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。
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