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skin color model
相关语句
  肤色模型
     Face Detection Based on Skin Color Model and FCM Dynamic Clustering
     基于肤色模型和FCM动态聚类的人脸检测
短句来源
     A kind algorithms of human face detection based on Neural Network and Skin color model
     基于肤色模型和神经网络的人脸检测算法
短句来源
     Considering the non-linearity among chroma (Cb, Cr component) and luminance (Y component) of skin color in the high and low luminance region, the skin color model is constructed by two lookup tables in Y-Cb and Y-Cr subspaces.
     考虑到在高亮度区和低亮度区肤色色度(Cb,Cr分量)与亮度(Y分量)非线性相关,采用Y- Cb和Y- Cr两个子空间的查询表来建立肤色模型
短句来源
     Considering the non-linearity among chroma (Cb, Cr component) and luminance (Y component) of skin color in the high and low luminance region, the skin color model is constructed by two lookup tables in Y-Cb and Y-Cr subspaces.
     考虑到在高亮度区和低亮度区肤色色度(Cb,Cr分量)与亮度(Y分量)非线性相关,采用Y-Cb和Y-Cr两个子空间的查询表来建立肤色模型
     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 .
短句来源
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  皮肤颜色模型
     Driver’s face detection applies the human face skin color model.
     在驾驶员人脸检测方面,本文利用了人脸皮肤颜色模型的驾驶员人脸检测方法。
短句来源
     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。
短句来源
     Face location is the key issue in the driver behavior surveillance Investigation indicates that face skin color has specifically distributing characteristic in the special color space In order to realize the face location in real time and solve the uncertainty problem caused by turning of the head,an algorithm for locating the face based on the skin color model is proposed in this paper Algorithm utilizes the distributing characteristic of the face shin color to pick?
     在采用计算机视觉对驾驶员进行驾驶行为监测时 ,面部定位是关键技术之一。 研究表明人脸皮肤颜色分量在特定颜色空间内具有特定的分布特性 ,为了解决人脸定位的实时性以及头部旋转不确定性等问题 ,本文给出了一种基于皮肤颜色模型的人脸定位算法。
短句来源
  “skin color model”译为未确定词的双语例句
     Then,we build a skin color model in YCbCr color space using the convergent property of skin color,and we present the Gaussian Model Skin Recognition Method and Positive-Negative Look-up Table Method in details.
     然后,利用皮肤颜色的聚合性,在YCbCr颜色空间建立了皮肤的颜色模型,并分别阐述了基于高斯分布模型的皮肤检测法和正反概率表方法;
短句来源
     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。
短句来源
     This paper constructs a skin color model in the YC_bC_r space based on a survey of face detection algorithms and experiments on color spaces of RGB,HSV and YC_bC_r.
     针对复杂彩色背景下的人脸检测问题,主要研究基于色彩信息的人脸检测算法,通过对RGB,HSV,YCbCr空间色彩模型分别做实验对比,选取在YCbCr空间进行人脸建模;
短句来源
     Experiments with a detection system show that the detection algorithm is robust to color distortion and is also able to be applied to face detection in gray images,and the algorithm can speed-up face detection and can promote detection correct rate to some degree compared with the detection algorithms based on skin color model and template matching.
     实验表明,该方法对图像偏色有一定的鲁棒性并可以用于灰度图像的人脸检测,而且检测正确率和速度比基于肤色和模板匹配的方法有了一定的改进。
短句来源
     First, a skin color model in HSI chrominance space is used for segmenting regions in which may have faces, and then the average-face based template matching and neural network verifying methods are used for searching faces in those regions.
     首先使用 HSI空间的肤色统计模型分割出可能包含人脸的区域 ,然后使用平均脸模板匹配和人工神经网验证的方法在这些区域中搜索人脸 .
短句来源
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  skin color model
We build a skin color model with Gaussian distribution and segment face region for each frame of incoming image stream.
      
With this Gaussian skin color model, we segment face region for each frame of the video, so we can obtain face image stream.
      
We use the images from internet to learn the skin-color model.
      
We also reported a comprehensive analysis of the Bayesian skin color model together with several interesting results.
      
The skin color region is extracted based on the skin color model.
      
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A robust real time face tracking algorithm for tele conference, tele education, surveillance and monitoring was presented. The face motion could be estimated by using face skin color model integrated with feature based object recognition technique and extended Kalman filter. The system worked at video rate, that is, 25 Hz for NTSC images and 30 Hz for PAL images. The experimental testing showed that the tracking algorithm worked well in complex environment and social occlusion...

A robust real time face tracking algorithm for tele conference, tele education, surveillance and monitoring was presented. The face motion could be estimated by using face skin color model integrated with feature based object recognition technique and extended Kalman filter. The system worked at video rate, that is, 25 Hz for NTSC images and 30 Hz for PAL images. The experimental testing showed that the tracking algorithm worked well in complex environment and social occlusion case.

提出用于电视电话会议、远程教学、监视与监控等场合的人脸实时跟踪方法 .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 .该方法有效地保证了复杂场景下目标跟踪的准确性 ,实现了带遮挡情况下的人脸实时跟踪 .系统跟踪速度达到视频速度 ,对于 PAL制式的视频图像达 30帧 /s,对于 NTSC制式的视频图像达 2 5帧 /s.

For speech recognition systems under noisy environment, lip reading technique can effectively reduce the influence of noise and improve the accurate rate of speech recognition system by adding visual information to acoustic channel. In this paper, an effective and robust approach for lip and mouth locating and tracking is presented to enable the information extraction under abnormal illumination and without special marks. This approach first locates face region with skin color model,...

For speech recognition systems under noisy environment, lip reading technique can effectively reduce the influence of noise and improve the accurate rate of speech recognition system by adding visual information to acoustic channel. In this paper, an effective and robust approach for lip and mouth locating and tracking is presented to enable the information extraction under abnormal illumination and without special marks. This approach first locates face region with skin color model, then finds the eyes from the face region with iterative algorithm, modifies the position and size of face according to the position of eyes, transforms the lower part of face by specific color coordinators to clearly distinguish lip color from skin color, and finally describes the outline of upper lip and lower lip with deformable template.

在许多应用于有噪声环境下的语音识别系统中 ,唇读技术能有效地降低噪声的影响 ,通过视觉通道来补充仅取决于听觉通道的信息量 ,从而提高语音识别系统的识别率 .该文提出了一种有效和稳健的唇定位跟踪方法 ,以满足不用特殊标识物和规范性照明就能对信息进行有效提取的应用需求 .该方法首先用肤色模型查找脸 ;然后用迭代算法搜索脸部区域内的眼睛 ;再根据眼睛的位置来确定脸的大小和位置 ,并对脸的下半部分采用彩色坐标变换法将唇从肤色中明显地区分出来 ;最后 ,用可变模板将上下唇的内外轮廓描述出来 .

In this paper, a face detection algorithm for color images based on skin color and template, which is composed of skin color segmentation, template matching, and neural network verifying is presented. First, a skin color model in HSI chrominance space is used for segmenting regions in which may have faces, and then the average-face based template matching and neural network verifying methods are used for searching faces in those regions. This algorithm integrates skin color information in...

In this paper, a face detection algorithm for color images based on skin color and template, which is composed of skin color segmentation, template matching, and neural network verifying is presented. First, a skin color model in HSI chrominance space is used for segmenting regions in which may have faces, and then the average-face based template matching and neural network verifying methods are used for searching faces in those regions. This algorithm integrates skin color information in color images with template matching and neural network classification model in gray level images, which results in not only faster speed, but also higher robustness of the algorithm. Experimental results demonstrate the efficiency and feasibility of this algorithm.

针对彩色图像提出了一种基于肤色和模板的人脸检测方法 ,由肤色分割、模板匹配和人工神经网验证 3部分组成 .首先使用 HSI空间的肤色统计模型分割出可能包含人脸的区域 ,然后使用平均脸模板匹配和人工神经网验证的方法在这些区域中搜索人脸 .该方法将彩色图像的肤色信息和灰度图像的模板匹配及人工神经网分类模型综合起来 ,既极大地提高了速度 ,又具有较强的鲁棒性 .实验结果表明 ,该算法是快速而有效的 .

 
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