PPT-Face Recognition based on 2D-PCA and CNN

Author : alida-meadow | Published Date : 2017-07-10

hongliang xue Motivation Face recognition technology is widely used in our lives Using MATLAB ORL database Database The ORL Database of Faces taken between

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Face Recognition based on 2D-PCA and CNN: Transcript

hongliang xue Motivation Face recognition technology is widely used in our lives Using MATLAB ORL database Database The ORL Database of Faces taken between April 1992 and April 1994 at the Cambridge University Computer . By Zhang . Liliang. Main idea: good features are no enough. VOC07: mAP:35.1. % -> 58.5%. Overview. (1) the model of R-CNN. (2) the result of R-CNN. (3) some discussions. Visualizing learned feature in CNN. using Convolutional Neural Network and Simple Logistic Classifier. Hurieh. . Khalajzadeh. Mohammad . Mansouri. Mohammad . Teshnehlab. Table of Contents. Convolutional Neural . Networks. Proposed CNN structure for face recognition. Motivation – Shape Matching. What is the best transformation that aligns the unicorn with the lion?. There are tagged feature points in both sets that are matched by the user. Motivation – Shape Matching. Recall Toy . Example. Empirical . (Sample). EigenVectors. Theoretical. Distribution. & Eigenvectors. Different!. Connect Math to Graphics (Cont.). 2-d Toy Example. PC1 Projections. Best 1-d Approximations of Data. Weihong Deng (. 邓伟洪. ). Beijing Univ. Post. & Telecom.(. 北京邮电大学. ) . 2. Characteristics of Face Pattern. The facial shapes are too similar, sometimes identical ! (~100% face detection rate, kinship verification). Yunchao. Wei, Wei Xia, . Junshi. Huang, . Bingbing. Ni, Jian Dong, Yao Zhao, Senior Member, IEEE . Shuicheng. Yan, Senior Member, IEEE. 2014. . arXiv. IEEE. . Short Papers. . HCPIssue. Date: Sept. 1 2016. By Blake Ellis and Melanie Hicken, Senior Writers . Email us at watchdog@cnn.com. watchdog@cnn.com. Deep Learning for Expression Recognition in Image Sequences Daniel Natanael García Zapata Tutors: Dr. Sergio Escalera Dr. Gholamreza Anbarjafari April 27 2018 Introduction and Goals Introduction Dennis Hamester et al., “Face ExpressionRecognition with a 2-Channel ConvolutionalNeural Network”, International Joint Conference on Neural Networks (IJCNN), 2015. 16/03/2011. 1. Rui. Min. Multimedia Communications Dept.. EURECOM. Sophia . Antipolis. , France. min@eurecom.fr. Abdenour. . Hadid. . Machine Vision Group. University of Oulu. Oulu, Finland. hadid@ee.oulu.fi. September 10, 2018. North Korean Parade. Mice, Ticks, and Lyme Disease. CNN 10. September 11. CNN 10. September 12, 2018 . Why Hurricane Florence is Uniquely Dangerous. CNN Hero Helps Children Worldwide. Hao Zhang. Computer Science Department. 1. Problem Statement. Verification. Identification. A. B. Same / Different persons?. A. B. C. D. Which has the same identity as A?. 2. Solutions. Extensions of still face recognition algorithms. th. , 2014. Eigvals. and . eigvecs. Eigvals. + . Eigvecs. An eigenvector of a . square matrix. A is a . non-zero. vector V that when multiplied with A yields a scalar multiplication of itself by . Jiali. . Duan. , . Shengcai. Liao, . Shuai. . Zhou. , . and Stan Z. Li. Center . for Biometrics and Security . Research. Institute . of Automation, Chinese Academy of . Sciences. Introduction. Face detection: foundations . Paper ID: 8762. K. M. Naimul Hassan. , Md. Shamiul . Alam. . Hridoy. , Naima Tasnim, . Atia. . Faria. Chowdhury, Tanvir . Alam. Roni, Sheikh Tabrez, Arik . Subhana. , Celia Shahnaz. Department of Electrical and Electronic Engineering (EEE),.

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