face detection recognition ppt
TRANSCRIPT
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Shri Siddhi Vinayak Institute Of Technology
Face Detection & RecognitionPresented ByMohd ShakirKamender Singh GangwarPrakher AwasthiKusum Lata
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Contents
Face Detection Face Detection 2 Face Recognition Face Recognition 2 Face detection & Recognition problems
Face detection problem structureFeature extraction processes.What is recognition?
Face recognition processingFace Recognition from videoClassification The Basic Idea Experimentation and Results System Overview
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Main
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FACE DETECTION
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FACE DETECTION 2
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FACE RECOGNIZE
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FACE RECOGNIZATION 2
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Face detection v3b*Face detection & recognition
Face detectionFace recognition
Face detectionFace recognitionMr.chang
Prof..ChengFace databaseOutput:
Face detection v3b
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CSE 576, Spring 2008Face Recognition and Detection*Face detection & Recognition problemsIdentity recognitionWhere is it?Object detection
Face Recognition and Detection
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The input of a face recognition system is always an image or video stream.The output is an identification or verification of the subject or subjects thatappear in the image or video. Some approaches define a face recognitionsystem as a three step process -A generic face recognition system
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Face detection problem structure
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Feature extraction processes.
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What is recognition?Where is this particular object?
What kind of object(s) is(are) present?
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Face Recognition by Humans Performed routinely and effortlessly by humans Enormous interest in automatic processing of digital images and videos due to wide availability of powerful and low-cost desktop embedded computing Applications: biometric authentication,surveillance, human-computer interactionmultimedia management
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Face recognition processingA face is a three-dimensional object subject to varying illumination, pose, expression is to be identified based on its two-dimensional image ( or three- dimensional images obtained by laser scan).
A face recognition system generally consists of 4 modules - detection, alignment, feature extraction, and matching.
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Face Recognition from video.Register w.r.t a SubspaceSelecting the most discriminative samples.
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*Classification A face recognition system is expected to identify faces present in imagesand videos automatically. It can operate in either or both of twomodes:Face verification (or authentication): involves a one-to-one match that compares a query face image against a template face image whose identity is being claimed.
Face identification (or recognition): involves one-to-many matches that compares a query face image against all the template images in the database to determine the identity of the query face.
First automatic face recognition system was developed by Kanade 1973.
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EE465: Introduction to Digital Image Processing Copyright Xin Li'2003*The Basic IdeaWe should easily recognize the point by looking through a small windowShifting a window in any direction should give a large change in intensity
EE465: Introduction to Digital Image Processing Copyright Xin Li'2003
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Experimentation and Results
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System Overview
The procedure for Face recognition is as follows. 1. Pre processing: The image is rescaled and the noise is reduced, contrast was normalized with histogram equalization.. 2. RobustPCA: The images then are applied with RobustPCA for reduction in dimensionality and there by reducing complexity. 3. Modified RBFN: The outputs of Robust PCA are applied to RBFN for classification , separation of faces and non faces and for training.
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REFRENCES[1] M. Turk, A. Pentland, Eigen faces for Recognition, Journal of Cognitive Neuroscience, Vol. 3, No. 1, Win. 1991, pp. 71-86 [2] Discriminant analysis for recognition of human face images Kamran Etemad and Rama Chellappa [3] MPCA: Multilinear Principal Component Analysis of Tensor Objects, Haiping Lu, Student Member, IEEE, Konstantinos N. (Kostas) Plataniotis, Senior Member, IEEE, and Anastasios N. Venetsanopoulos, Fellow, IEEE [4] Face detection Inseong Kim, Joon Hyung Shim, and Jinkyu Yang
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