PPT-Face Recognition

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. The face image is divided into several regions from which the LBP feature distributions are extrac ted and concatenated into an enhanced feature vector to be used as a face descriptor Th e performance of the proposed method is assessed in the face r . Modelling. . and. . Recognition. . Survey. Timur Aksoy. Biometrics. . Course. . Fall. 2011. Sabanci. . University. Outline. Background. Approaches. Average. . Face. Model. Iterative. . Closest. Simon Wood. @MrSimonWood. Recording.... We . record our sessions. http://walesdtc.ac.uk/onlinematerials. But what about the live experience?. Asking questions?. Discussion?. (On Air). Welsh Video Network/JVCS. Microsoft Corporate. ganghua@microsoft.com. Online Contextual Face Recognition: . Towards Large Scale Photo Tagging for Sharing. Photo sharing has become a main online social activity. FaceBook. receives 850 million photo uploads/month. Shengcai. Liao. NLPR, CASIA. April 29, 2015. Background. Cooperated face recognition. People are asked to stand in front of a camera with good illumination conditions. Border pass, access control, attendance, etc.. Linda Shapiro. CSE 455. 1. Face recognition: once you’ve detected and cropped a face, try to recognize it. Detection. Recognition. “Sally”. 2. Face recognition: overview. Typical scenario: few examples per face, identify or verify test example. Student: . Yikun. Jiang. . Professor: Brendan Morris. Outlines. Introduction of Face Recognition. The . Eigenface. Approach. Relationship to Biology and Neutral Networks. 2. Question to Consider. What are the key challenges police officers face when dealing with persons in behavioral crisis?. 3. Recognizing a. Person in Crisis. Crisis Recognition. 4. Behavioral Crisis: A Definition. 2. Question to Consider. What are the key challenges police officers face when dealing with persons in behavioral crisis?. 3. Recognizing a. Person in Crisis. Crisis Recognition. 4. Behavioral Crisis: A Definition. cogch2 pt 2. 2. Disorders . of Object Recognition. AGNOSIA.  : a general term for a loss of ability to recognize objects, people, sounds, shapes, or smells. . Agnosias result from damage to . cortical areas . 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. Linda Shapiro. CSE 455. 1. Face recognition: once you’ve detected and cropped a face, try to recognize it. Detection. Recognition. “Sally”. 2. Face recognition: overview. Typical scenario: few examples per face, identify or verify test example. Linda Shapiro. ECE P 596. 1. What’s Coming. Review of . Bakic. flesh . d. etector. Fleck and Forsyth flesh . d. etector. Review of Rowley face . d. etector. Overview of. . Viola Jones face detector with . AdaBoost. Linda Shapiro. CSE 455. 1. What’s Coming. The basic . AdaBoost. algorithm (next). The Viola Jones face . d. etector features. The modified . AdaBoost. algorithm that is used in Viola-Jones face detection.