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Review of Cognition in Learning and Memory by Lee Gregg, editor, Department of Education, University of Cininnati, in American Scientist.

Review of Cognition in Learning and Memory by Lee Gregg, editor, Department of Education,... REVIEWS ii U N D E R S T A N D I N G NATURAL LANGUAGE by Terry Winograd; reviewed by Rermert H. Clark, Psychology American Scientist, J a n u a r y - F e b r u a r y 197~, PP i18-11~. COGNITION IN LEARNING AND MEMORY Lee Gregg, editor; reviewed by Daniel D. Wheeler, Department in American Scientist, J a n u a r y - f e b r u a r y 1974, p. 119. Department, Stanford University, in ila of ~ducatlon, Unlversity o~ Cincinnati, AlP VISdAL INFORMATION PROCESSING Proceedings of a symposium, Pittsburgh, ~ay 1~72, William G. Chase, ~ditor; revieweo Neisser, Center for Advanced Study in the behavioral Sciences, Stanford, California, Vol. I~3, February i, 197~. PATTERN RECOGNITION, L ARNING, AND THOUGHT by Leonard Unr; reviewed by Earl Hunt, Departments of Psychology Washington, Seattle, in SCIENCe, Vcl. 183, February i, 197h. by Ulric in SCIENCe, 1c and Computer Science, University o Ala ABSTRACTS A. THE by ~arK GENERAL ABSTRACTS A2a INT RACTIVE GENERATION OF FACIAL IMAGES ON A CRT USING A HEURISTIC STRATEGY Lee Gillenson 197h Ph.D. Thesis Department of Computer and Information Science The Ohio State University Columbus, OIIio ~Ketching a human face is a task which involves spatial Oecisions and a Knowledge Of the aspects of the face that are important in recognition. These are talents WhiCh n o n - a r t i s t s lack. This d i s s e r t a t i o n describes the design and i m p l e m e n t a t i o n ol a m a n - m a c h i n e system with which a n o n - a r t i s t can create, on a graphic display, any male Caucasian facial image from a photograph in front of him. The computer system contains pro-stored facial features, an average face used as a starting point, and a neuristic strategy which provides the user with the "now-to-do-it" Knowledge necessary. The user makes all of the visual aecisions and makes changes in the displayed image hy adjusting analog input devices. The face is subdivided into 17 features, 7 of which are paired, e.g., the ears. Stored in the system are several variations of each feature. These are desiguea such that given the c a p a b i l i t i e s of the hardware to scale, translate, and rotate images, any reasonable v a r i a t i o n can oe achieved for any of the features. The strategy includes some global heuristics in addition to a p r e d e t e r m i n e d sequence of operations. The user always works in the context of one continually upuated face on the CRT. The sequence o f operations is such that the most important changes in terms o f recognition a r e maue first in an attempt to home-in on the target as quickly as possible. The user c o m m u n i c a t e s wltn the system through the analog devices and through single letter or number responses on the a l p h a n u m e r i c terminal, and so is not requires to Know any programming or %o type long instructions. The system begins oy displaying a m a t h e m a t ~ c a l l y c a l c u l a t e d average face on the CR~. First the user is asked to estimate the target's age and an aging process tares place. Then a pair o f large scale stretching routines are used to secure the gross shape of the ace. Furtner, gross changes are made next on individual features or sets of features througn a n l e r a r c n l c a l m a n i p u l a t i o n scheme. Following this there begins a series of "retrieval" routines. The user is asked questions about each feature and a new version of the feature is retrieved %rom memory and displayed on the G ~ . It is set at the same scale and position as the previously displayed version o f that feature and can then be further m a n i p u l a t e d by the user, In between any pair o retrieval routines the user can i n t e r r u p t to the h i e r a r c h y or to any feature retrieval routine out of its usual order. Finally, curly, wavY, or straight hair are added through the use of special routines and the eyebrows and eyeballs are filled in. Experiments were conducted which showed that for an arbitrary non-artls%, nls results on the system in an attempt to sketch a face ~rom a photograph, were superior to his results using pencil and paper. page i~ April 197~ SIGART ,aWS&~T~R http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGART Bulletin Association for Computing Machinery

Review of Cognition in Learning and Memory by Lee Gregg, editor, Department of Education, University of Cininnati, in American Scientist.

ACM SIGART Bulletin , Volume (45) – Apr 1, 1974

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Publisher
Association for Computing Machinery
Copyright
Copyright © 1974 by ACM Inc.
ISSN
0163-5719
DOI
10.1145/1045220.1045227
Publisher site
See Article on Publisher Site

Abstract

REVIEWS ii U N D E R S T A N D I N G NATURAL LANGUAGE by Terry Winograd; reviewed by Rermert H. Clark, Psychology American Scientist, J a n u a r y - F e b r u a r y 197~, PP i18-11~. COGNITION IN LEARNING AND MEMORY Lee Gregg, editor; reviewed by Daniel D. Wheeler, Department in American Scientist, J a n u a r y - f e b r u a r y 1974, p. 119. Department, Stanford University, in ila of ~ducatlon, Unlversity o~ Cincinnati, AlP VISdAL INFORMATION PROCESSING Proceedings of a symposium, Pittsburgh, ~ay 1~72, William G. Chase, ~ditor; revieweo Neisser, Center for Advanced Study in the behavioral Sciences, Stanford, California, Vol. I~3, February i, 197~. PATTERN RECOGNITION, L ARNING, AND THOUGHT by Leonard Unr; reviewed by Earl Hunt, Departments of Psychology Washington, Seattle, in SCIENCe, Vcl. 183, February i, 197h. by Ulric in SCIENCe, 1c and Computer Science, University o Ala ABSTRACTS A. THE by ~arK GENERAL ABSTRACTS A2a INT RACTIVE GENERATION OF FACIAL IMAGES ON A CRT USING A HEURISTIC STRATEGY Lee Gillenson 197h Ph.D. Thesis Department of Computer and Information Science The Ohio State University Columbus, OIIio ~Ketching a human face is a task which involves spatial Oecisions and a Knowledge Of the aspects of the face that are important in recognition. These are talents WhiCh n o n - a r t i s t s lack. This d i s s e r t a t i o n describes the design and i m p l e m e n t a t i o n ol a m a n - m a c h i n e system with which a n o n - a r t i s t can create, on a graphic display, any male Caucasian facial image from a photograph in front of him. The computer system contains pro-stored facial features, an average face used as a starting point, and a neuristic strategy which provides the user with the "now-to-do-it" Knowledge necessary. The user makes all of the visual aecisions and makes changes in the displayed image hy adjusting analog input devices. The face is subdivided into 17 features, 7 of which are paired, e.g., the ears. Stored in the system are several variations of each feature. These are desiguea such that given the c a p a b i l i t i e s of the hardware to scale, translate, and rotate images, any reasonable v a r i a t i o n can oe achieved for any of the features. The strategy includes some global heuristics in addition to a p r e d e t e r m i n e d sequence of operations. The user always works in the context of one continually upuated face on the CRT. The sequence o f operations is such that the most important changes in terms o f recognition a r e maue first in an attempt to home-in on the target as quickly as possible. The user c o m m u n i c a t e s wltn the system through the analog devices and through single letter or number responses on the a l p h a n u m e r i c terminal, and so is not requires to Know any programming or %o type long instructions. The system begins oy displaying a m a t h e m a t ~ c a l l y c a l c u l a t e d average face on the CR~. First the user is asked to estimate the target's age and an aging process tares place. Then a pair o f large scale stretching routines are used to secure the gross shape of the ace. Furtner, gross changes are made next on individual features or sets of features througn a n l e r a r c n l c a l m a n i p u l a t i o n scheme. Following this there begins a series of "retrieval" routines. The user is asked questions about each feature and a new version of the feature is retrieved %rom memory and displayed on the G ~ . It is set at the same scale and position as the previously displayed version o f that feature and can then be further m a n i p u l a t e d by the user, In between any pair o retrieval routines the user can i n t e r r u p t to the h i e r a r c h y or to any feature retrieval routine out of its usual order. Finally, curly, wavY, or straight hair are added through the use of special routines and the eyebrows and eyeballs are filled in. Experiments were conducted which showed that for an arbitrary non-artls%, nls results on the system in an attempt to sketch a face ~rom a photograph, were superior to his results using pencil and paper. page i~ April 197~ SIGART ,aWS&~T~R

Journal

ACM SIGART BulletinAssociation for Computing Machinery

Published: Apr 1, 1974

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