Description: 介绍当前所有人脸技术的改进工作.包手肤色建模,Adaboost训练,Suan算法等改进算法.-Introduced all the current technology to improve the working face. Packet hand color model, Adaboost training, Suan algorithm to improve the algorithm. Platform: |
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Author:hante |
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Description: 鲁棒人脸跟踪系统学位论文；提出了一种两阶段的光照均衡的方法来消除单幅图像中的各种阴影包括模糊阴影，投射阴影等 根据快速的Adaboost 训练框架，本文提出了一个实时的鲁棒人脸检测算法 提出了一种基于在线实值boosting 的方法来处理人脸在跟踪过程中发生的外貌变化；实现了一个基于以上模块的完全自动化的人脸跟踪器-Robust Face Tracking System dissertation proposes a two-stage light-balanced approach to the elimination of single image in a variety of shadow including fuzzy shadow, projected shadow, etc. Under the fast-track the Adaboost training framework, this paper presents a real-time Robust Face Detection Algorithm Based on boosting online real ways to deal with people face in tracking occurred during the appearance of change the realization of a module based on the above fully automated face tracker Platform: |
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Author:田卉 |
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Description: adaboost的实现算法，可进行人脸的样本训练-implementation of the AdaBoost algorithm, can be a sample of people face training Platform: |
Size: 227328 |
Author:yinxin |
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Description: this document explains the process of training a pedestrian detector using Viola and Jones’
cascaded classifier approach. it was originally Platform: |
Size: 132096 |
Author:lordthanatos |
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Description: Adaboost训练分类器的源代码，是快速人脸检测的必备。-It is the code for training classifiers by
Adaboost to Face Detection Platform: |
Size: 7360512 |
Author:杨果 |
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Description: 基于支持向量机的人脸检测训练集增强算法实现。根据支持向量机(support vector machine，简称SVM)~ ，对基于边界的分类算"~(geometric approach)~
言，类别边界附近的样本通常比其他样本包含有更多的分类信息．基于这一基本思路，以人脸检测问题为例．探讨了
对给定训练样本集进行边界增强的问题，并为此而提出了一种基于支持向量机和改进的非线性精简集算法
IRS(improved reduced set)的训练集边界样本增强算法，用以扩大-91l练集并改善其样本分布．其中，所谓IRS算法是指
在精简集(reduced se0算法的核函数中嵌入一种新的距离度量一一图像欧式距离一一来改善其迭代近似性能，IRS
可以有效地生成新的、位于类别边界附近的虚拟样本以增强给定训练集．为了验证算法的有效性，采用增强的样本
集训练基于AdaBoost的人脸检测器，并在MIT+CMU正面人脸测试库上进行了测试．实验结果表明通过这种方法
能够有效地提高最终分类器的人脸检测性能．-According to support vector machines(SVMs)，for those geometric approach based classification
methods，examples close to the class boundary usually are more informative than others．Taking face detection as an
example，this paper addresses the problem of enhancing given training set and presents a nonlinear method to tackle
the problem effectively．Based on SVM and improved reduced set algorithm (IRS)，the method generates new
examples lying close to the face／non—face class boundary to enlarge the original dataset and hence improve its
sample distribution．The new IRS algorithm has greatly improved the approximation performance of the original
reduced set(RS)method by embedding a new distance metric called image Euclidean distance(IMED)into the
keme1 function．To verify the generalization capability of the proposed method，the enhanced dataset is used to train
an AdaBoost．based face detector and test it on the MIT+CMU frontal face test set．The experimental results show
that the origina Platform: |
Size: 649216 |
Author:郭事业 |
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Description: 一篇在人脸检测时用于训练反面训练集的文章，可以-A face detection in the negative training set for training the article, you can see Platform: |
Size: 4679680 |
Author:jarry |
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Description: 人脸检测根据姿态评估，然后利用adaboost方法训练分类器，是一片值得收藏的文章-Face detection based on posture assessment and classification using adaboost training method, is a worthy collection of articles Platform: |
Size: 3933184 |
Author:程志林 |
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Description: 基于adaboost的人脸检测算法,包括训练，修改了数据读取结构，降低了内存需求-Based on adaboost face detection algorithms, including training, to modify the data read structure, reducing the memory requirements Platform: |
Size: 14336 |
Author:alvin |
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Description: 基于ADABOOST的人脸检测代码，使用继承的策略，包括特征的计算，提取，ADABOOST训练，级联，最后训练出数据，还有注释，可以帮助大家研究ADBOOST-face detection code based on ADABOOST using inheritance strategies, and it includs the calculation and extraction of features, the training and cascade of ADABOOST, and the data will be trained out at last,annotations is also given as well , it can help you research ADBOOST Platform: |
Size: 13312 |
Author:薛 |
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Description: 针对LBP的人脸检测算法的文章3篇，区别于adaboost的人脸检测算法，opencv有相应的训练数据库。-For three of the articles of the LBP face detection algorithm, the face detection algorithm is different from adaboost, opencv training database. Platform: |
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Author: |
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Description: 关于adaboost算法的人脸检测程序，可以选择不同的训练库进行检测，对adaboost算法的理解有好处。-AdaBoost algorithm of face detection program, you can choose different training library for testing, good understanding of the AdaBoost algorithm. Platform: |
Size: 472064 |
Author: |
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Description: 一个基于adaboost的人脸检测分类器训练程序，用MMATLAB写的，希望能和大家分享，已通过测试。
-Based on the human face detection adaboost classifier training procedures, written in MMATLAB, and we hope to share, has been tested. Platform: |
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Author:坚定 |
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Description: this codes is Source code for face detection of viola paper.of its Features is:
Feature Computation: The “Integral” image representation
Feature Selection: The AdaBoost training algorithm .
Real-timeliness: A cascade of classifiers.-this codes is Source code for face detection of viola paper.of its Features is:
Feature Computation: The “Integral” image representation
Feature Selection: The AdaBoost training algorithm .
Real-timeliness: A cascade of classifiers.
Platform: |
Size: 420864 |
Author:fatemeh |
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Description: 由一个3D变形人脸模型取自动生成适应的训练样本。由统计视角，tailored训练数据保证了所有的数据变化且由任意的人脸属性丰富训练样本，例如，年龄或体重。更进一步，它可能自动适应到环境约束，例如，来自于监控摄像机的照明或视角约束。我们使用裁剪的（tailor）图象训练一个新的Viola Jones的adaboost 目标检测框架的多核实现。这个新的实现不仅快速的，而且多特征通道的使用成为可能，例如，在训练期间的颜色特征。在我们实验中，我们训练7个依赖视角的人脸检测子并在Face Detection Data Set 和 Benchmark (FDDB)中评估它们。- takes a look
into the automated generation of adaptive training samples
a 3D morphable face model. Using statistical insights,
the tailored training data guarantees full data variability
and is enriched by arbitrary facial attributes such as age
or body weight. Moreover, it can automatically adapt to
environmental constraints, such as illumination or viewing
angle of recorded video footage surveillance cameras.
We use the tailored imagery to train a new many-core implementation of Viola Jones’ AdaBoost object detection framework. The new implementation is not only faster but also
enables the use of multiple feature channels such as color
features at training time. Platform: |
Size: 1202176 |
Author:郭继东 |
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Description: 使用pca方法对图像进行特征提取，对训练集的20个人的共一百张人脸进行训练，使用adaboost算法生成强分类器，可以对测试集的人脸图片进行识别，且识别率较高(The PCA method is used to extract the features of the image, and the training is carried out for a total of 100 faces of 20 people in the training set. The AdaBoost algorithm is used to generate a strong classifier, which can recognize the face images in the test set with a high recognition rate) Platform: |
Size: 19835904 |
Author:王二愣子 |
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Search - adaboost training face