NDLI: Effecting an Improvement to the Fitness Function. How to Evolve a More Identifiable Face

Content Provider	IEEE Xplore Digital Library
Author	Frowd, C. Park, J. McIntyre, A. Bruce, V. Pitchford, M. Fields, S. Kenirons, M. Hancock, P.J.B.
Copyright Year	2008
Description	Author affiliation: Dept. of Psychol., Univ. of Central Lancashire, Preston (Frowd, C.)
Abstract	Constructing the face of a criminal from the selection of individual facial parts is a hard task. We have been working on a new system called EvoFIT that involves the selection and breeding of complete faces. The approach is theoretically better founded and produces more identifiable composites than those from a traditional 'feature' system. In the current paper, we explored three new methods of presenting faces to a person using EvoFIT. A better quality face was evolved if (1) the external parts of the face were subjected to a Gaussian blur, allowing a user to focus on the important inner region of the face, (2) if the faces were simplified to make them sketch-like in appearance, and (3) if users took longer in deciding which faces to select for breeding. Taken together, these approaches would appear to make a marked improvement in the ability to evolve an identifiable likeness of a target.
Starting Page	3
Ending Page	10
File Size	805085
Page Count	8
File Format	PDF
ISBN	9780769532653
DOI	10.1109/BLISS.2008.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-04
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Face recognition Psychology Construction industry Videos witness evolve face recognition crime GA Face facial composite Facial features
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Evolving the Face of a Criminal: How to Search a Face Space More Effectively

Automating the Processes Involved in Facial Composite Production and Identification

Facial Composite Production Using EFITV

Towards robust face recognition from multiple views

Dynamic facial expression recognition using autoregressive models

An efficient approach for recognizing and tracking spontaneous facial expressions

Facial Expression Recognition using AAM and Local Facial Features

Dynamic Weighting of Facial Features for Automatic Pose-Invariant Face Recognition

Recognizing Facial Expressions in Videos Using a Facial Action Analysis-Synthesis Scheme

Effecting an Improvement to the Fitness Function. How to Evolve a More Identifiable Face

Similar Documents

Evolving the Face of a Criminal: How to Search a Face Space More Effectively

Automating the Processes Involved in Facial Composite Production and Identification

Facial Composite Production Using EFITV

Towards robust face recognition from multiple views

Dynamic facial expression recognition using autoregressive models

An efficient approach for recognizing and tracking spontaneous facial expressions

Facial Expression Recognition using AAM and Local Facial Features

Dynamic Weighting of Facial Features for Automatic Pose-Invariant Face Recognition

Recognizing Facial Expressions in Videos Using a Facial Action Analysis-Synthesis Scheme

Effecting an Improvement to the Fitness Function. How to Evolve a More Identifiable Face