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skin color segmentation
相关语句
  肤色分割
     Based on skin color segmentation and wavelet transform,a novel method is presented for the detection of human face in color images.
     本文针对人脸检测过程中常用到的基于彩色图像肤色分割的方法存在的不足,提出了一种将彩色图像肤色分割方法与图像的小波变换方法相结合的人脸区域检测方法。
短句来源
     In this thesis , a face detection system based on certain project is built to detect single face in color image with simple background which integrates the skin color segmentation, face template matching and region optimization .
     本文针对简单背景下的彩色单人脸图像,将肤色分割、模板匹配与区域优化工作结合起来,构建了一个基于工程实际的人脸检测系统,并对复杂背景和多人脸图像情况下的检测进行了一定探讨。
短句来源
     Fast Human Face Detection Based on Skin Color Segmentation and Neural Network Verification
     基于肤色分割和神经网络确认的快速人脸检测
短句来源
     Face Detection Based on Skin Color Segmentation,Region Analysis and Template Distribution
     基于肤色分割、区域分析和模板分布的人脸检测研究
短句来源
     To avoid the background interference, skin color segmentation can be applied in order to enhance the accuracy of eye detection.
     为了避免图像背景对人眼检测的干扰,还运用了肤色分割原理来缩小检测人眼的搜索区域,从而进一步提高人眼定位的准确性。
短句来源
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  “skin color segmentation”译为未确定词的双语例句
     A Method of Human Face Detection in Color Image Using Skin Color Segmentation
     一种基于肤色分割的彩色图像人脸检测算法
短句来源
     For increasing the speed of detecting human face, a fast face detection method based on skin color segmentation is proposed.
     为了提高人脸检测速度,提出了一种基于肤色分割的快速人脸检测方法.
短句来源
     Especially, the multiple-scaled various classifications scheduled face detection algorithm takes information between frames, skin color segmentation, and eyes detection to get coarse results. And then, different features were used according to the different sizes of detection windows.
     研究了一种多尺度指导的多分类器调度人脸检测算法,该算法在综合使用帧间信息和肤色信息以及人眼点检测作为粗筛选,在粗筛选的基础上根据分析窗口的大小选择不同的分类器和特征进行人脸的检测,充分考虑了分辨率对人脸特征的影响。
短句来源
     The first step is construct the Gaussian Model for skin color under YCbCr and get the likely region of face, then skin color segmentation is carry out with the method of dynamic threshold optimizing.
     在YCbCr色彩空间中建立肤色分布的高斯模型,得到肤色概率似然图像,在最佳动态阈值选取算法下完成肤色区域的分割。
短句来源
     Students’head and shoulder images are acquired through the combination of background difference and frames difference. Applied skin color segmentation based on YCb ' Cr ' color space, we got a rough face area.
     研究首先通过背景差分和帧间差分实现了学生头肩部图像提取,之后选择基于YCb ' Cr '颜色空间的肤色模型实现了快速人脸定位。
短句来源
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  相似匹配句对
     The color of the skin and its measurement
     皮肤的颜色及其测量
短句来源
     The Features of Skin Color
     人体的肤色特征
短句来源
     skin
     皮肤
短句来源
     COLOR
     冬季女装色彩预测
短句来源
     Face Detection Based on Segmentation of Skin Color
     基于肤色分割的人脸检测
短句来源
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  skin color segmentation
With 25 eigenfaces, a 74% average accuracy was achieved after calibration on skin color segmentation.
      
The skin-color segmentation and change detection techniques are presented in sections 2 and 3, respectively.
      
The subject's actions are segmented using a skin-color segmentation algorithm followed by an unsupervised clustering algorithm.
      
The majority of the incorrectly clustered action models represent failures of the skin-color segmentation.
      
The algorithm consists of three steps, namely skin-color segmentation, change detection and VOP generation.
      
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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 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 .

This paper presents a survey on the state of the art of face detection research based on systematic analysis of related papers. Firstly face detection problem is divided into several classes according to the type of input images, background complexity, pose variance, application domain etc., and then face pattern is analyzed based on various features and their possible fusion method for the purpose of face detection. The literature is reviewed in two parts: feature extraction and feature fusion for face detection....

This paper presents a survey on the state of the art of face detection research based on systematic analysis of related papers. Firstly face detection problem is divided into several classes according to the type of input images, background complexity, pose variance, application domain etc., and then face pattern is analyzed based on various features and their possible fusion method for the purpose of face detection. The literature is reviewed in two parts: feature extraction and feature fusion for face detection. Feature extraction includes skin color segmentation and various gray level features such as the outline of face, gray level distribution, organic feature, symmetry, template etc. Feature fusion methods include knowledge based heuristic face verification, statistical learning approaches (Eigenface, Clustering, ANN, SVM, HMM, EM probabilistic model). Performance comparison of some well known methods is given on MIT+CMU test set. In conclusion, statistical learning methods are superior to those knowledge based methods, and in all those learning based methods, the key problem is the training complexity, even by bootstrap method it remains a great challenge due to the diversity of non face samples compared with face samples. We suggest a subspace method for downsizing the training space by designing a filter (such as template matching filter) that excludes most of non face candidates and then training in the downsized subspace. It is pointed out that statistical learning methods depend on the accordance of sample patterns (syntactic information), which cannot take into considerations of much important semantic information. This differs much from human beings in face cognition. There is a limit for statistical only approaches and the help of knowledge based methods is needed.

人脸检测问题最初作为自动人脸识别系统的定位环节被提出 ,近年来由于其在安全访问控制、视觉监测、基于内容的检索和新一代人机界面等领域的应用价值 ,开始作为一个独立的课题受到研究者的普遍重视 .该文从人脸检测问题的分类、人脸模式的分析、特征提取与特征综合、性能评价等角度 ,系统地整理分析了人脸检测问题的研究文献 ,将人脸检测方法主要划分为基于知识的人脸验证方法和基于统计的学习方法 ,指出统计学习方法优于启发式验证方法

A Dominant Face retrieval system for news videos is presented in this paper.Firstly,the news video is segmented into shot series,then a trained face detector is applied to each shot to get some candidate face regions,then subjected to rule -based selection,for the purpose to get highly creditable face regions as samples for skin color modeling of the current shot.After skin color segmentation,the candidate regions are checked against the reasonable position,size,and face templates.Passed regions are...

A Dominant Face retrieval system for news videos is presented in this paper.Firstly,the news video is segmented into shot series,then a trained face detector is applied to each shot to get some candidate face regions,then subjected to rule -based selection,for the purpose to get highly creditable face regions as samples for skin color modeling of the current shot.After skin color segmentation,the candidate regions are checked against the reasonable position,size,and face templates.Passed regions are viewed as human faces and added into the tracking list,followed by the bidirectional face tracking.Correction will be periodically conducted after tracking every certain number of frames,to reduce the accumulated error and detect new faces timely.For higher accuracy in detection and later recognition,this paper constructs a specific skin color model,rather than the general shot color model,for each object in tracking list.When tracking finished,the system will try to find the best face image of each face series for recognition.At last,the PCA algorithm combined with individual skin color model comparison is used to determine which one is the target face.

该文针对新闻视频设计并实现了一个显著人脸检索系统。首先将新闻视频分割成镜头序列,利用训练好的CascadeAdaboost人脸检测器对每个镜头检测出一定数目的候选人脸,按照一些规则选取可信度高的作为样本,用于提取该镜头内的肤色模型。接着对肤色分割后的区域进行位置、大小分析和模板匹配,以淘汰非人脸区域,确定待跟踪的对象列表。为了做精确的跟踪和识别,系统对每个跟踪对象建立更细致的肤色模型。跟踪过程中每间隔一定帧数重新进行人脸检测,以减少误差积累和探测是否有新人脸出现。最后从每个人脸序列挑选最适合进行人脸识别的图像建立其特征脸空间,结合肤色信息和PCA算法判断其是否为要检索的目标人脸。

 
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