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Description: 本课题的主要内容是图像预处理,它主要从摄像头中获取人脸图像然后进行处理,以便提高定位和识别的准确率.该模块主要包含光线补偿、图像灰度化、高斯平滑、均衡直方图、图像对比度增强，图像预处理模块在整个系统中起着极其关键的作用，图像处理的好坏直接影响着后面的定位和识别工作,内有源代码和全部论文资料-this issue is the major content of image preprocessing, mainly from the camera to obtain images Face then, in order to improve the recognition and positioning accuracy. The module consists mainly of light compensation, Grayhound, Gaussian smoothing, balanced histogram, image contrast enhancement, image pre- processing module in the system plays a crucial role in image processing will have a direct impact behind the positioning and identification, within Active code and all papers information
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Size: 2281472 |
Author: 陈万通 |
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Description: OpenCV Color Histogram.
Draw Color Histogram from the input image.
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Size: 1119232 |
Author: yaling |
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Description: 人脸的检测与定位：相似度计算-二值化-垂直直方图-水平直方图-标记人脸区域-Face Detection and Positioning: Similarity Computing- Binarization- Vertical Histogram- level histogram- labeled human face of regional
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Size: 470016 |
Author: Chen Dengwu |
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Description: 本文介绍了一种灰色图像识别中进行人眼睛定位的算法,首先是根据人脸的水平灰度直方图来确定眼睛的位置,然后,
通过计算眼眶部分像素点的垂直灰度直方图来确定两眼中心,接着从获得的区域中找出一定数量的灰度值小的点,对这些点进行添加、删除和计算,实现眼睛的定位．-In this paper, a gray image recognition in the human eye location algorithm, the first is based on the level of facial histogram to determine the location of the eyes, and then, by calculating the orbital part of the vertical pixel histogram to determine the two Eye Center, and then from the region access to a certain number of gray value to identify a small point, on these points add, delete, and calculated to achieve the positioning of the eyes.
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Size: 1664000 |
Author: 闫慧 |
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Description: A new approach toward target representation and localization, the central component in visual tracking
of non-rigid objects, is proposed. The feature histogram based target representations are regularized
by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions
suitable for gradient-based optimization, hence, the target localization problem can be formulated using
the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya
coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the
presented tracking examples the new method successfully coped with camera motion, partial occlusions,
clutter, and target scale variations. Integration with motion filters and data association techniques is also
discussed. We describe only few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking .
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Size: 2779136 |
Author: |
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Description: 人脸识别提出的LBP特征计算程序，简单实用的特征，可以得到统计的直方图特征-LBP features of face recognition proposed by the calculation procedure, simple and practical features of the histogram statistics can be characteristic of
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Size: 3072 |
Author: changxin.gao |
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Description: This a MFC program to test direct linear discriminant analysis (direct LDA) for face recognition. Histogram equalization is used as a preprocessing and direct LDA is used to reduce a dimension in feature space from train images. Minimum Euclidean distance is used for face recognition of test images. -This is a MFC program to test direct linear discriminant analysis (direct LDA) for face recognition. Histogram equalization is used as a preprocessing and direct LDA is used to reduce a dimension in feature space from train images. Minimum Euclidean distance is used for face recognition of test images.
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Size: 8902656 |
Author: SUNGWOONG KIM |
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Description: face recognition by using histogram matching
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Size: 4327424 |
Author: ahmed |
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Description: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects,
is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The
masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem
can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as
similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method
successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data
association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.
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Size: 2459648 |
Author: Ali |
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Description: 基于Processed histogram的人脸识别方法，方法简单，识别率高，参考文献“Face Recognition using processed histogram and phase only correlation”-Recognizing objects from large image databases, histogram based methods have proved simplicity and usefulness in last decade. Initially, this idea was based on color histograms that were launched by swain. This algorithm presents the first part of our proposed technique named as “Histogram processed Face Recognition”.
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Size: 4342784 |
Author: GJ |
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Description: 使用boosting,edge orientation histogram和cascade算法实现face detection的文章。解决了使用小数据库训练系统和区分肖像画的问题。-The use of boosting, edge orientation histogram and the cascade algorithm face detection article. Solution using a small database, training systems and the distinction between portraiture issues.
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Size: 521216 |
Author: 刘洋 |
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Description: 眨眼检测，先用haar特征框定人脸，然后用camshift跟踪人脸，根据几何特征得到人眼的大概位置，然后根据直方图的变化检测眨眼-Blink detection, the first feature with the haar framed face, and then use camshift tracking human face, according to the geometric features are the approximate location of the human eye, and then change detection histogram blink of an eye
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Size: 5120 |
Author: 阿强 |
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Description: Histogram face recognition in matlab code
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Size: 3507200 |
Author: bluesky871 |
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Description: LBP人脸识别：基于对小波分解和局部二进制模式(LBP)分析，提出了一种多级LBP直方图的序列特征(M—HSLBP)的提取方法。-LBP Face Recognition: Based on the wavelet decomposition and local binary pattern (LBP) analysis, a multi-stage sequence of LBP histogram features (M-HSLBP) extraction method.
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Size: 339968 |
Author: 石业晨 |
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Description: 完整的包括皮肤及动作识别的C++人脸检测源代码，涉及的技术有：小波分析，尺度缩减模型（PCA,LDA,ICA），人工神经网络（ANN），支持向量机（SVM），SSE编程，图像处理，直方图均衡，图像滤波，C++编程等。-Complete, including skin and actions identified C++ face detection source code, the technology involved are: wavelet analysis, scaling down model (PCA, LDA, ICA), artificial neural network (ANN), support vector machine (SVM), SSE Programming , image processing, histogram equalization, image filtering, C++ programming.
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Size: 462848 |
Author: 黄大伟 |
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Description: 基于Matlab 直方图Histogram的人脸识别程序：给出人脸图像库，包含训练及测试模块，最终给出识别结果。文件中附介绍。-Histogram Histogram for Face Recognition Based on Matlab program: given face image database that contains training and testing modules, and ultimately gives the recognition results. Described in the attached file.
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Size: 3594240 |
Author: sangsang |
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Description: 基于Matlab+直方图Histogram的人脸识别程序-Histogram Histogram based on Matlab+ Face Recognition program
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Size: 3528704 |
Author: 陈扬洋 |
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Description:
基于直方图的人脸检测，GUI用户界面-Histogram-based face detection, GUI user interface
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Size: 3635200 |
Author: 戈薇 |
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Description: Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application
domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of Oriented Gradients, i.e. HOG, features. A K-mean clustering technique is used in a cascade of HOG feature classifiers to detect faces. The evaluation of the algorithm shows similar performance in terms of detection rate as state of the art algorithms. Moreover, unlike state of the art algorithms,our system can be quickly trained before detection is possible. Performance is considerably increased in terms of lower computational cost and lower false detection rate when combined with motion constraint given by moving objects in video sequences. The detected HOG features are integrated within a tracking framework and allow reliable face tracking results in several tested surveillance video sequences.
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Size: 293888 |
Author: linuszhao |
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Description: This program is used for face recognition which uses color histogram method
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Size: 361472 |
Author: Kushal |
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