sdm SDM 人脸对齐的核心内容很简单,就是特征到偏移量的映射: Ix = R I 是特征,x是映射矩阵,R是偏移量.SDM人脸对齐方法训练的目的就是得到映射矩阵x,步骤如下: )归一化样本,使样本的尺度统一: )计算均值人脸: )将均值人脸,作为估计人脸放在样本上,使均值中心和原始人脸形状中心对齐: )计算基于每一个均值人脸的标记点的特征,sift,surf或者…
最近组里研究了SDM算法在人脸对齐中的应用,是CMU的论文<Supervised Descent Method and its Applications to Face Alignment>.因为思路简洁巧妙有效,两年下来引用率就有283+了,以后估计1k+,这么有影响力的文章是要学习学习.网上有了相关的原理介绍,例如:http://www.thinkface.cn/thread-2913-1-1.html.自己看了有所了解,但不能真正理解原理思路,还是直接看论文为妥. .问题 ).Hessi…
对于face recognition的研究,我是认真的(认真expression,哈哈哈~~~~~~)许久没有写blog了,欢迎一起讨论. SDM(Supvised Descent Method)方法主要是应用在人脸对齐上.SDM本是一种求函数逼近的方法,可以用于最小二乘求解.SDM并非一种人脸对齐方法,只是作者在提出新的人脸对齐方法中运用了自己的最小二乘方法.文章:Supervised Descent Method and its Applications to Face Alignment.…
When performing inverse kinematics (IK) on a complicated bone chain, it can become too complex for an analytical solution. Cyclic Coordinate Descent (CCD) is an alternative that is both easy to implement and efficient to process.逆运动学问题一般采用解析法和基于Jacob…
本文译自<Deep learning for understanding faces: Machines may be just as good, or better, than humans>.为了方便,文中论文索引位置保持不变,方便直接去原文中找参考文献. 近些年深度卷积神经网络的发展将各种目标检测和识别问题大大的向前推进了不少.这同时也得益于大量的标注数据集和GPU的使用,这些方面的发展使得在无限制的图片和视频中理解人脸,自动执行诸如人脸检测,姿态估计,关键点定位和人脸识别成为了可能.本…
利用Landmarks进行人脸对齐裁剪是人脸检测中重要的一个步骤.效果如下图所示: 基本思路为: a.人脸检测 人脸的检测不必多说了,基本Cascade的方式已经很不错了,或者用基于HOG/FHOG的SVM/DPM等.这些在OpenCV,DLIB都有. b.在检测到的人脸上进行Landmarks检测,获得一系列的Landmark点 对齐算法很多,特别是前几年人脸对齐获得了巨大的成功. [1].One Millisecond Face Alignment with an Ensemble of R…
源地址:http://www.learnopencv.com/facial-landmark-detection/#comment-2471797375 OCTOBER 18, 2015 BY SATYA MALLICK 51 COMMENTS Facial landmark detection using Dlib (left) and CLM-framework (right). Who sees the human face correctly: the photographer, the…
@http://www-cs-faculty.stanford.edu/people/karpathy/cvpr2015papers/ CVPR 2015 papers (in nicer format than this) maintained by @karpathy NEW: This year I also embedded the (1,2-gram) tfidf vectors of all papers with t-sne and placed them in an interf…
From: http://www.pamitc.org/cvpr15/program.php Official Program for CVPR 2015 Monday, June 8 8:30am-8:40am Ballrooms A,B,C Rooms 302,304,306 Opening Remarks from Conference Chairs The opening remarks will be made from Ballrooms A,B,C, but a live vid…
cvpr所有文章 http://cs.stanford.edu/people/karpathy/cvpr2015papers/ CNN Hypercolumns for Object Segmentation and Fine-Grained LocalizationBharath Hariharan, Pablo Arbeláez, Ross Girshick, Jitendra Malik Improving Object Detection With Deep Convolutional…
what has been done: This paper proposed a novel Deep Supervised Hashing method to learn a compact similarity-presevering binary code for the huge body of image data. Data sets: CIFAR-10: 60,000 32*32 belonging to 10 mutually exclusively categories(6…
solver : {‘newton-cg’, ‘lbfgs’, ‘liblinear’, ‘sag’}, default: ‘liblinear’ Algorithm to use in the optimization problem. For small datasets, ‘liblinear’ is a good choice, whereas ‘sag’ is faster for large ones. For multiclass problems, only ‘newton-cg…
http://www.cv-foundation.org/openaccess/CVPR2016.py ORAL SESSION Image Captioning and Question Answering Monday, June 27th, 9:00AM - 10:05AM. These papers will also be presented at the following poster session 1 Deep Compositional Captioning: Descr…
What are the advantages of different classification algorithms? For instance, if we have large training data set with approx more than 10000 instances and more than 100000 features ,then which classifier will be best to choose for classification Want…
CVPR2016 Paper list ORAL SESSIONImage Captioning and Question Answering Monday, June 27th, 9:00AM - 10:05AM. These papers will also be presented at the following poster session 1 Deep Compositional Captioning: Describing Novel Object Categories Witho…
##Linear Regression with One Variable Linear regression predicts a real-valued output based on an input value. We discuss the application of linear regression to housing price prediction, present the notion of a cost function, and introduce the gradi…
What: 就是将统计学算法作为理论,计算机作为工具,解决问题.statistic Algorithm. How: 如何成为菜鸟一枚? http://www.quora.com/How-can-a-beginner-train-for-machine-learning-contests 链接内容总结: "学习任何一门学科,framework是必不可少的东西.没有framework的东西,那是研究." -- Jason Hawk One thing is for sure; you ca…
When a golf player is first learning to play golf, they usually spend most of their time developing a basic swing. Only gradually do they develop other shots, learning to chip, draw and fade the ball, building on and modifying their basic swing. In a…
Ha, it's English time, let's spend a few minutes to learn a simple machine learning example in a simple passage. Introduction What is machine learning? you design methods for machine to learn itself and improve itself. By leading into the machine lea…
Brief History of Machine Learning My subjective ML timeline Since the initial standpoint of science, technology and AI, scientists following Blaise Pascal and Von Leibniz ponder about a machine that is intellectually capable as much as humans. Famous…
CVPR2015 Papers震撼来袭! CVPR 2015的文章可以下载了,如果链接无法下载,可以在Google上通过搜索paper名字下载(友情提示:可以使用filetype:pdf命令). Going Deeper With ConvolutionsChristian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke…
BRIEF HISTORY OF MACHINE LEARNING My subjective ML timeline (click for larger) Since the initial standpoint of science, technology and AI, scientists following Blaise Pascal and Von Leibniz ponder about a machine that is intellectually capable as muc…
