Description: This thesis relates to the design, implementation and evaluation of statis¬ tical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition rates are maintained. Platform: |
Size: 1726464 |
Author:ivan |
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Description: An automatic facial feature extraction method is
presented in this paper. The method is based on the edge
density distribution of the image. In the preprocessing stage a
face is approximated to an ellipse, and genetic algorithm is
applied to search for the best ellipse region match. In the
feature extraction stage, genetic algorithm is applied to
extract the facial features, such as the eyes, nose and mouth,
in the predefined sub regions. The simulation results
validates that the proposed method is capable of
automatically extracting features from various video images
effectively under natural lighting environments and in the
presence of certain amount of artificial noise and of multi-
face oriented with angles.-An automatic facial feature extraction method is
presented in this paper. The method is based on the edge
density distribution of the image. In the preprocessing stage a
face is approximated to an ellipse, and genetic algorithm is
applied to search for the best ellipse region match. In the
feature extraction stage, genetic algorithm is applied to
extract the facial features, such as the eyes, nose and mouth,
in the predefined sub regions. The simulation results
validates that the proposed method is capable of
automatically extracting features from various video images
effectively under natural lighting environments and in the
presence of certain amount of artificial noise and of multi-
face oriented with angles. Platform: |
Size: 324608 |
Author:fais |
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Description: 人脸识别是模式识别研究领域的重要课题, 目前是一个非常活跃的研究方向。人脸识别中一个最重要的过程就是特征检测与提取, 因为眼睛、鼻子和嘴巴等特征集中了人脸的大部分信息。因此对于人脸识别中的特征提取来说, 不仅要检测出这些特征, 而且要准确地加以定位。眼睛是人脸识别中包含特征信息最多的器官, 对它的精确定位是后续特征提取的前提和基础, 而其精度更是直接影响到整个系统的识别率, 所以一个有效、快速和精确的人眼定位方法是非常重要的。-Face recognition pattern recognition research is an important issue, is currently a very active research. Face recognition is one of the most important process feature detection and extraction, because the eyes, nose and mouth and other features focused on the face of most of the information. Therefore, feature extraction for face recognition, not only to detect these features, but also to accurately locate. The eyes are the face recognition feature information contained in the largest organ, the follow-up to its precise positioning is the prerequisite and basis for feature extraction, and its accuracy is even more direct impact on the recognition rate of the entire system, so an effective, fast and accurate human Eye positioning is very important. Platform: |
Size: 4304896 |
Author:江霞 |
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Description: 研究优化人脸特征提取问题，针对长期以来在不贴标记点的情况下用传统的光流、Snake、可变模板等方法对纹理特征变化大的特征点不能有效跟踪，并且解决单独采用Gabor 小波系统开销大等问题，为了在人脸图像中提取准确信息，提出了人脸特征点的跟踪方法，分组采用改进的光流法和弹性图匹配的方法进行特征点跟踪。对眼睛、眉毛、上下眼皮等14 个表
情变化不大的特征点使用光流法进行跟踪，最后对变化大的嘴部8 个特征点运用Gabor 小波的弹性图匹配方法进行仿真。-Gabor wavelet research to optimize facial feature extraction problem for a long time in the case of stickers marked point changes of texture features with traditional optical flow, Snake, variable template feature points can not effectively track and solve alone overhead and large, in order to extract the accurate information in a face image, the facial feature point tracking method, grouping, improved optical flow method and elastic graph matching feature point tracking. Little change in the feature point of eyes, eyebrows, and eyelids 14 expression using the optical flow method for tracking simulation using Gabor wavelet elastic graph matching method, and finally on the changes of eight characteristic points of the mouth portion. Platform: |
Size: 444416 |
Author:yaomeng |
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Search - eyes features extraction