Description: 深入浅出介绍计算机视觉的最新动态。内容包括：
* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration
* Extracting camera motion and scene structure from image sequences
* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms
* Image-based lighting for illuminating scenes and objects with real-world light images
* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more
* Face detection, alignment, and recognition--with new solutions for key challenges
* Perceptual interfaces for integrating vision, speech, and haptic modalities
* Development with the Open Source Computer Vision Library (OpenCV)
* The new SAI framework and patterns for architecting computer vision applications Platform: |
Size: 12192309 |
Author:kankan |
Hits:
Description: 深入浅出介绍计算机视觉的最新动态。内容包括：
* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration
* Extracting camera motion and scene structure from image sequences
* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms
* Image-based lighting for illuminating scenes and objects with real-world light images
* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more
* Face detection, alignment, and recognition--with new solutions for key challenges
* Perceptual interfaces for integrating vision, speech, and haptic modalities
* Development with the Open Source Computer Vision Library (OpenCV)
* The new SAI framework and patterns for architecting computer vision applications-Easy to introduce the latest developments in computer vision. Include:* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration* Extracting camera motion and scene structure from image sequences* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms* Image-based lighting for illuminating scenes and objects with real-world light images* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more* Face detection, alignment, and recognition- with new solutions for key challenges* Perceptual interfaces for integrating vision, speech, and haptic modalities* Development with the Open Source Computer Vision Library (OpenCV)* The new SAI framework and patterns for architecting computer vision applications Platform: |
Size: 12191744 |
Author:kankan |
Hits:
Description: This code implement method described in paper Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions Platform: |
Size: 52224 |
Author:bach |
Hits:
Description: This a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex. -This is a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex.
Platform: |
Size: 2751488 |
Author:minu |
Hits:
Description: This a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex. -This is a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex.
Platform: |
Size: 14336 |
Author:minu |
Hits:
Description: 近年来，面部识别技术已经备受关注，其研究已迅速，因为它有许多在计算机视觉通讯和控制系统，自动存取的应用潜力。特别是，人脸检测是一种面部识别作为自动人脸识别第一步的重要组成部分。
然而，人脸检测并不简单，因为它需要用到许多技术，如构成变化（前，非前），闭塞，形象定位，照明条件和面部表情的变化-In recent years, face recognition technology has been concern that its research has rapidly because it has many computer vision, communication and control system, automatic access to potential applications. In particular, face detection is a kind of face recognition automatic face recognition as an important part of the first step.
However, face detection is not simple, because it needs to use many techniques, such as changes in the composition (the former, non-ago), occlusion, image orientation, lighting conditions and facial expression changes .... Platform: |
Size: 443392 |
Author:lll |
Hits:
Description: 基于形态学商图像的光照归一化算法.复杂光照条件下的人脸／P,~J1是一个困难但需迫切解决的问题，为此提出了一种有效的光照归一化算法．
该方法根据面部光照特点，基于数学形态学和商图像技术对各种光照条件下的人脸图像进行归一化处理，并且将它
发展到动态地估计光照强度，进一步增强消除光照和保留特征的效果．与传统的技术相比，该方法无须训练数据集以
及假定光源位置，并且每人只需一幅注册图像，在耶鲁人脸图像库B上的测试表明，该算法以较小的计算代价取得了
优良的识别性能．-Face recognition under complex illumination conditions is still an open question．To cope with the
problem ，this paper proposes an effective illumination normalization method．The proposed method employs
morphology and quotient image techniques by analyzing the face illumination，and it is upgraded with dynamical
lighting estimation technique to strengthen illumination compensation and feature enhancement．Compared with
traditional approaches，this method doesn’t need any training data and any assumption on the light conditions，
moreover，the enrollment requires only one image for each subject．The proposed methods are evaluated on Yale
Face database B and receive a very competitive recognition rate with low computational cost． Platform: |
Size: 299008 |
Author:郭事业 |
Hits:
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 |
Hits:
Description: 基于matlab的人脸识别分析，参考文献为：
[1] X.Tan and B.Triggs. Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions, In Proceedings of the 2007 IEEE International Workshop on Analysis and Modeling of Faces and
Gestures -Matlab-based face recognition analysis, references to: [1] X. Tan and B. Triggs. Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions, In Proceedings of the 2007 IEEE International Workshop on Analysis and Modeling of Faces and Gestures Platform: |
Size: 44032 |
Author:透明 |
Hits:
Description: Gamma intensity correction is on of preprocessing technique in face recognition. Using Gamma
intensity correction face images are preprocessed to normalize the lighting variation. The overall
brightness of the image can be controlled by changing the gamma parameter. Platform: |
Size: 70656 |
Author:murthy |
Hits:
Description: The 3-D Morphable Model was
introduced as a generative model to p redictthe appearances o f
an individual while using a statistical prior on shape and
texture allowin g its parameters to be estimated from single
image. Based on these new unde rstandings , face recognition
algorithms have been developed to address the joint challenges of pose and lighting. Platform: |
Size: 1209344 |
Author:bobobobo |
Hits:
Description: 正在完善，需要下载资料，先上传上去，人脸识别，最终实现动态识别。arm板子提供图像数据，我用的是arm11.完成后上传最终版本.通过tinyos系统的nesc语言的板子实现手机远程控制灯光-Is perfect, you need to download data, first upload up, face recognition, and ultimately achieve dynamic identification. arm board provides image data, I use arm11. complete final version uploaded by tinyos system nesc the language of the board for mobile phone remote control lighting Platform: |
Size: 4260864 |
Author:dxy |
Hits:
Description: The demand for robust face recognition in real-world
surveillance cameras i ncreasing due to the needs of practical applications
such as security and surveillance. Although face recognition
has been studied extensively in the literature, achieving good
performance in surveillance videos with unconstrained faces i nherently
difficult. During the image acquisition process, the noncooperative
subjects appear in arbitrary poses and resolutions in
different lighting conditions, together with noise and blurriness
of images. In addition, multiple cameras are usually distributed
in a camera network and different cameras often capture a subject
in different views. In this paper, we aim at tackling this unconstrained
face recognition problem and utilizing multiple cameras
to improve the recognition accuracy using a probabilistic approach.
We propose a dynamic Bayesian network to incorporate
the information different cameras as well as the temporal
clues frames in a video sequence-The demand for robust face recognition in real-world
surveillance cameras is increasing due to the needs of practical applications
such as security and surveillance. Although face recognition
has been studied extensively in the literature, achieving good
performance in surveillance videos with unconstrained faces is inherently
difficult. During the image acquisition process, the noncooperative
subjects appear in arbitrary poses and resolutions in
different lighting conditions, together with noise and blurriness
of images. In addition, multiple cameras are usually distributed
in a camera network and different cameras often capture a subject
in different views. In this paper, we aim at tackling this unconstrained
face recognition problem and utilizing multiple cameras
to improve the recognition accuracy using a probabilistic approach.
We propose a dynamic Bayesian network to incorporate
the information different cameras as well as the temporal
clues frames in a video sequence Platform: |
Size: 1774592 |
Author:manthiramm |
Hits:
Description: 基于Yale-B和CMU-PIE 人脸库上的实验结果显示本文算法对复杂光照具有较强鲁棒性，具备提取复杂光照条件下人脸图像有效特征的能力。小波变换 特征提取 matlab仿真-Experimental results based on Yale-B and CMU-PIE face show that the proposed algorithm has a strong light on the complexity of robustness, with the extraction of complex lighting conditions in human face images effective feature capabilities. Wavelet transform feature extraction matlab simulation Platform: |
Size: 390144 |
Author:suca |
Hits:
Description: 智能图像/视频处理中，复杂背景环境（比如室外环境、机场、车站等）下，人脸识别的第一步是人脸的检测。它的精确度直接影响到后期识别的结果。不过，领域内的科学家们基本上很难有足够的精力和时间开发优化的C++代码，使其用于商业用途，而一般都是只在Matlab中进行模拟。
本文的目的是提供一个我开发的SSE优化的，C++库，用于人脸检测，你可以马上把它用于你的视频监控系统中。文章中的分类器的训练数据来自与我的 webcam图像，它们被采集于不同时间，不同光照，不同背景环境下，它几乎可以实时地检测出我（的脸：）。训练的非人脸数据来自对不同背景的采集，用的是同一个webcam。被提取出的人脸区域，已经经过下面的处理：高斯滤波，直方图均衡化。
如果你需要更精确的结果，请从internet上下载更多不同的人脸集合，然后从新训练分类器。和我的库中一样尺寸的公共库是CBCL，其库超过100MB，所以，请大家自己下载楼-Intelligent image/video processing, complex background environment (such as an outdoor environment, airports, stations, etc.), the first step is the recognition of face detection. It directly affects the accuracy of the latter part of the identification results. However, scientists in the field are basically difficult to have enough energy and time to develop optimized C++ code to be used for commercial purposes, and are generally only be simulated in Matlab. The purpose of this paper is to provide an optimized SSE my development, C++ library for face detection, you can immediately use it for your video surveillance system. Face article classifier training data with my webcam images, which are collected at different times, in different lighting, different background environment, it is almost real-time detection of me (a :). Training of non-face data collection different backgrounds, with the same webcam. Was extracted face region, has been subjected to the following treatment: Gaussi Platform: |
Size: 15348736 |
Author:周文活 |
Hits:
Description: We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression Platform: |
Size: 4096 |
Author:sheida |
Hits:
Description: Enhanced Local Texture Feature Sets for Face
Recognition under Difficult Lighting Condition light handle-Enhanced Local Texture Feature Sets for Face
Recognition under Difficult Lighting Condition light handle Platform: |
Size: 4096 |
Author:xiaoqiang |
Hits:
Description: 该方法利用人脸具有镜像对称的自然特性，依据奇偶分解原理，生成成镜像奇、偶对称样本，井利用人脸对称图像作为训练样本，再利用主分量分析(PCA)对训练样本进行二阶相关和降维处理，然后对处理后的样本进行ICA特征提取。理论和分析实验证明，该算法有效减线了人脸受到视角、光照、人脸表情、姿势变化等因素的最响，又增加了训练样本容量，减少了计算复杂度，同时有效解决了小样本问题，提高了识别率.(The method uses the natural characteristics of mirror symmetry of human face, generates mirror odd and even symmetrical samples according to the principle of parity decomposition, uses the symmetrical images of human face as training samples, then uses principal component analysis ( PCA ) to carry out second-order correlation and dimensionality reduction processing on the training samples, and then carries out ICA feature extraction on the processed samples. Theoretical and analytical experiments show that the algorithm can effectively reduce the face by the angle of view, lighting, facial expressions, posture changes and other factors, and increase the capacity of training samples, reduce the computational complexity, and effectively solve the problem of small samples, improve the recognition rate.) Platform: |
Size: 4099072 |
Author:廊下青衫 |
Hits:
Search - face recognition lighting