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Description: 人脸检测程序。在菜单上有许多功能选项，可实现多角度，多目的检测。-face detection procedures. In the menu options are many functions that can be achieved from different angles, multi-purpose testing.
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Size: 955392 |
Author: 李展望 |
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Description: A very good paper that explain tracking facial feature under varying face pose and facial expression-This paper presents a hierarchical multi-state pose-dependent approach for facial feature detection and tracking under varying facial expression and face pose. For effective and efficient representation of feature points, a hybrid representation that integrates Gabor wavelets and gray-level profiles is proposed. To model the spatial relations among feature points, a hierarchical statistical face shape model is proposed to characterize both the global shape of human face and the local structural details of each facial component. Furthermore, multi-state local shape models are introduced to deal with shape variations of some facial components under different facial expressions. During detection and tracking, both facial component states and feature point positions, constrained by the hierarchical face shape model, are dynamically estimated using a switching hypothesized measurements (SHM) model. Experimental results demonstrate that the proposed method accurately and robustly tracks faci
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Size: 958464 |
Author: Ng Jack |
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Description: 提出了一种多姿态知识模型, 并以之从人脸器官梯度图中获得候选脸的大小、位置、姿态类别和眼、嘴重心坐标, 然后
按姿态类别将候选脸与对应的模板进行匹配确认人脸. 该人脸检测算法集人脸检测、姿态估计和眼、嘴定位于一体, 具有检测速
度快的特点, 适于多姿态多人脸场合的人脸检测. 该算法只利用了图像的灰度信息, 因此对灰度图像和彩色图像的人脸检测均
适用.-Proposes a multi-gesture knowledge model, and to the organs of the gradient map from the human face to get the candidate face size, location, posture, type and eyes, mouth center coordinates, and then press the gesture categories will face a candidate to match with the corresponding template to confirm face. The set of face detection algorithms face detection, pose estimation, and eyes and mouth position in one, with detection of the characteristics of speed, suitable for Multi-pose face of occasions more than face detection. The algorithm uses only images grayscale information, so the grayscale images and color images of face detection apply.
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Size: 480256 |
Author: 天使 |
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Description: 基于LLR算法的多姿态人脸识别，是对以往的改进版本-LLR-based Multi-pose face recognition algorithm is an improved version of previous
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Size: 397312 |
Author: 刘同敏 |
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Description: 该人脸库包含30个人、每人10幅总共300幅光栅图像，每个人的10幅图像包括了朝正前方、朝左、朝右、朝上和朝下五种不同的视角
方向的情形，经典的多姿态人脸库
注意此文件为.ras格式，需要用ACDSEE打开，SUN光栅图片格式。-The face database contains 30 individuals, each 10 Total 300 raster images, 10 images of each person included toward the front, left, turn right, up and down direction of the perspective of five different situations, Classic Pose-face database Note that this file is. ras format, you need to open with ACDSEE, SUN raster image formats.
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Size: 63641600 |
Author: shirley |
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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: 基于Adaboost算法的多姿态人脸实时视频检测江苏大学-Adaboost algorithm based on multi-pose face detection real-time video
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Size: 283648 |
Author: xuxiaorui |
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Description: This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale
Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong
robustness to the expression, accessory, pose and illumination
variations. One MLP (Multi Layer Perceptron) based network is
adopted as classifier of SIFT keypoint feature. The proposed
classifier classifies each keypoint into face ID then an ID index histogram counting method is applied as the identification method to recognize face images. Also a bootstrapping method is investigated to select training images during training MLP. The performance of face recognition in some challenging databases is improved efficiently.
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Size: 122880 |
Author: tongliu |
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Description: 提出了一种针对复杂环境下的过人脸检测方法，首先在CbCgCr空间利用直接最小二乘法构建了对光照和复杂背景鲁棒性更好肤色聚类模型，实现了准确的肤色检测；然后针对人脸中姿态和表情变化，提出了基于Adaboost的多姿态人脸检测，精确的实现了人脸检测定位。-Extraordinary face detection method for complex environments, the first space CbCgCr direct least squares method to build a better robustness to light and complex background color clustering model to achieve accurate color detection forface, posture and facial expression changes, proposed the multi-pose face detection based on Adaboost, accurate face detection and location.
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Size: 5086208 |
Author: 洁洁 |
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Description: 一种处理多姿态人脸识别的多候选类加权识别方法-Weighted identification method for a treatment of multi-candidate class of multi-pose face recognition
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Size: 396288 |
Author: yang mei |
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Description: 针对神经网络的瓦斯预测模型存在的泛化性能差且存在易陷入局部最优的缺点，提出了
基于最小二乘支持向量机(LS-SVM)时间序列瓦斯预测方法．由于标准最小二乘支持向量机
(L孓SVM)要求样本误差分布服从高斯分布，且标准LS-SVM丧失鲁棒性与稀疏性等特点，提出
了基于加权LS-SVM的瓦斯时间序列预测的方法，从而提高了标准L孓SVM模型的鲁棒性．其
中时间序列的嵌入维数与延迟时间采用了微熵率最小原则进行选取，在此基础上给出了基于加
权L孓SVM实现多步时间序列预测的算法实现步骤．最后利用MATLAB 7．1对其进行仿真研
究，通过鹤壁十矿1个突出工作面的瓦斯涌出数据实例对模型进行了验证．结果表明，加权
SVM模型比标准的L§SVM明显提高了鲁棒性，可较好地实现时间序列数据的多步预测．-The neural network gas prediction model is poor in generalization performance and
easy in fafling into the local optimal value．In order to overcome these shortcomings，we pro—
pose the time series gas prediction method of least squares support vector machine(L§SVM)．
However，in the LS-SVM case，the sparseness and robustness may lose，and the estimation of
the support values iS optimal only in the case of a Gaussian distribution of the error variables．
So，this paper proposes the weighted L孓SVM tO overcome these tWO drawbacks．Meanwhile，
the optimal embedding dimension and delay time of time series are obtained by the smallest dif—
ferential entropy method．On this basis，multi-step time series prediction algorithm steps are
given based on the weighted LS-SVM．Finally，the data of gas outburst in working face of Hebi
lOth mine iS adopted to validate this model．The results show that the predict effect of shortterm
the face gas emission is better using the weighted LS-SVM model than using
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Size: 490496 |
Author: wanggen |
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Description: 本文运用深度神经网络的方法克服姿态变量和图像分辨率的影响,提出了一种多姿态的人脸超分辨识别算法并在实验数据集上获得了良好的性能表现。另外本文利用深度信念网络探索正面人脸图像和侧面人脸图像的映射,方法放松了深度信念网络的输入也输出之间绝对相等,而只是保证其高层含义上的相等。实验表明了使用深度信念网络可以学习到侧面人脸图像到正面人脸图像的一个全局映射,但是丢失了个体细节差异。本文还提出了基于深度网络保持姿态邻域进行姿态分类的方法,在学习过程中,我们保证了同一个姿态下的人脸图像应该与同一姿态下的多张图像互为邻居。实验证明了,我们的方法在用于姿态分类具有非常良好的性能,但是也发现学习过程中,那些与区别个体的信息逐渐丢失了,这也导致了直接运用非线性近邻元分析的特征的人脸识别的性能不佳。-In this paper, the neural network approach to overcome the depth of variables that affect the attitude and image resolution , proposed a multi-pose face recognition algorithms and super-resolution experimental data set obtained in a good performance. Also this paper to explore the depth of belief network mapping frontal face image and profile face images , the method of absolute equality between the input relax depth of belief networks is also output , but only to ensure equal meaning on its top . Experimental results show that the use of deep belief networks can learn to face image to the side of the front face of a global image map , but lost the details of individual differences . This paper also proposes to maintain posture neighborhood depth network-based gesture classification methods in the learning process , we ensure that the face image under the same gesture with multiple images should be under the same attitude are neighbors . Experiment proves that our method for gesture cl
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Size: 9719808 |
Author: cen |
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