Description: 对由光源颜色变化引起的图像色彩偏差,进行了校正,并在YCbCr颜色空间建立了Cb-Cr色度查找表和亮度信息联合的肤色模型,应用预处理技术,去除部分非人脸区域,减少人脸检测的搜索空间,并采用模板匹配方法在人脸候选区域检测人脸.实验表明,该方法能够有效的从复杂环境的彩色图像中检测出左右旋转不超过45°的人脸,且不受人脸表情、尺度和数目的影响,且错误率较低.-Color by the light source caused by the change of image color deviation, a correction, and YCbCr color space established a Cb-Cr chrominance and luminance information look-up table of the color model of the joint application of pre-treatment technology, to remove some non-human face region, Face detection to reduce the search space, using a template matching method in the face candidate region detection of human faces. experiments show that the method can be effective in complex environments from color images detected no more than about 45 ° rotation of the human face, and from Facial Expression, scale and number of impact, and lower error rate. Platform: |
Size: 191488 |
Author:lll |
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Description: 人脸识别MATLAB工具箱
Faces detection toolbox v 0.1 -This toolbox provides some tools for faces detection using Local Binary Patterns and Haar features.
The task of detection is done by boosting approaches such Adaboosting, FastAdaboosting and Gentleboosting.
The main objective of this toolbox is to deliver simple but efficient tools mainly written in C codes with
a matlab interface and easy to modify. Platform: |
Size: 18769920 |
Author:he si |
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Description: Face Detection
In this program you will choose a photo and program will detect faces in this photo Platform: |
Size: 4442112 |
Author:abc fdg |
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Description: 利用局部二位模式和haar特征进行人脸或目标识别。-This toolbox provides some tools for objects/faces detection using Local Binary Patterns (and some variants) and Haar features.
Object/face detection is performed by evaluating trained models over multi-scan windows with boosting models
(such Adaboosting, FastAdaboosting and Gentleboosting) or with linear SVM models.
The main objective of FDT is to bring simple but efficient tools mainly written in C codes with a matlab interface and easy to modify. Platform: |
Size: 18237440 |
Author:zhu rg |
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Description: 人脸检测与跟踪是一个重要而活跃的研究领域，它在视频监控、生物特征识别、视频编码等领域有着广泛的应用前景。该项目的目标是在FPGA板上实现实时系统来检测和跟踪人脸。人脸检测算法包括肤色分割和图像滤波。通过计算被检测区域的质心来确定人脸的位置。该算法的软件版本独立实现，并在matlab的静止图像上进行测试。虽然从MATLAB到Verilog的转换没有预期的那样顺利，实验结果证明了实时系统的准确性和有效性，甚至在不同的光线、面部姿态和肤色的条件下也是如此。所有硬件实现的计算都是以最小的计算量实时完成的，因此适合于功率受限的应用。(Face detection and tracking is an important and active research field, and it has a wide range of applications in video surveillance, biometrics, video coding and other fields. The goal of the project is to implement real-time systems on the FPGA board to detect and track faces. Face detection algorithms include skin segmentation and image filtering. The location of the human face is determined by calculating the centroid of the detected region. The software version of the algorithm is implemented independently and tested on MATLAB still images. Although the conversion from MATLAB to Verilog is not as smooth as expected, the experimental results demonstrate the accuracy and effectiveness of real-time systems, even in different light, facial gestures and color conditions. All hardware implementations are performed in real-time with minimal computational complexity and are therefore suitable for power constrained applications.) Platform: |
Size: 63488 |
Author:合发
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