Computer-based retrieval of witnessed faces using inter-feature similarity

KOHEI ADACHI

doi:10.4992/psycholres1954.36.233

KOHEI ADACHI

Author information

Keywords: automated information retrieval, witnesses, face perception, stimulus similarity, feature description, vector model

JOURNAL FREE ACCESS

1994 Volume 36 Issue 4 Pages 233-238

DOI https://doi.org/10.4992/psycholres1954.36.233

Details

Published: December 21, 1994 Received: December 11, 1992 Available on J-STAGE: February 24, 2009 Accepted: January 08, 1994 Advance online publication: - Revised: -
Correction information
Date of correction: February 24, 2009 Reason for correction: - Correction: ABSTRACT Details: Wrong : This paper presents a computer-based system for retrieving a witnessed face from a database of faces. To construct the database, a male adult was asked to observe 100 male adult faces one by one on a TV monitor and describe the features of each face using a set of 605 descriptors which had been collected in the previous study. Feature descriptors thus chosen for each face are stored in the database. A computer algorithm calculates a similarity value between a description by a witness and the stored description of each face, to search for the faces which match the witness's description- The similarity is defined as a function of inter-feature similarities, using a vector representation of features. These inter-feature similarities are obtained from either human ratings or statistical correlations. An experimental evaluation of the system using 12 college students as “witnesses” gave promising results.
Right : This paper presents a computer-based system for retrieving a witnessed face from a database of faces. To construct the database, a male adult was asked to observe 100 male adult faces one by one on a TV monitor and describe the features of each face using a set of 605 descriptors which had been collected in the previous study. Feature descriptors thus chosen for each face are stored in the database. A computer algorithm calculates a similarity value between a description by a witness and the stored description of each face, to search for the faces which match the witness's description The similarity is defined as a function of inter-feature similarities, using a vector representation of features. These inter-feature similarities are obtained from either human ratings or statistical correlations. An experimental evaluation of the system using 12 college students as “witnesses” gave promising results.

Date of correction: February 24, 2009 Reason for correction: - Correction: AFFILIATION Details: Wrong :
1) National Research Institute of Police Science

Right :
1) Notional Research Institute of Police Science

Date of correction: February 24, 2009 Reason for correction: - Correction: CITATION Details: Wrong : Adachi, K., Watanabe, S., & Suzuki, A. 1992 Retrieval of faces from features described by eyewitnesses. Japanese Journal of Psychology, 63, 55-59. (In Japanese with English Summary)
Bruce, V., & Burton, M. 1989 Computer recognition of faces. In A. W. Young & H. B. Ellis (Eds.), Handbook of research on face processing. Amsterdam: North-Holland. Pp. 487-506.
Goldstein, A. J., Harmon, L. D., & Lesk, A. B. 1972 Man-machine interaction in human-face identification. Bell System Technical Journal, 51, 399-427.
Laughery, K. R., Rhodes, B. T., Jr. & Batten, G. W., Jr. 1981 Computer-guided recognition and retrieval of facial images. In G. Davies, H. Ellis & J. Shepherd (Eds.), Perceiving and remembering faces. London: Academic Press. Pp. 251-269.
Salton, G., & McGill, M. J. 1983 Introduction to modern information retrieval. New York: McGraw-Hill.
Shepherd, J. W. 1986 An interactive computer system for retrieving faces. In H. D. Ellis, M. A. Jeeves, F. Newcombe & A. Young (Eds), Aspects of face processing. Dordrecht: Martinus Nijhoff. Pp. 398-409.
Suzuki, A., Watanabe, S., & Adachi, K. 1991 Effects of reporting style, seeing condition and different target on retrieval accuracy. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 59-66. (In Japanese with English Summary)
Tversky, A. 1977 Features of similarity. Psychological Review, 84, 327-352.
Watanabe, S., Adachi, K., & Suzuki., A 1991 Retrieval of facial images using rating scales with standard stimuli. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 168-175. (In Japanese with English summary)

Right : Adachi, K., Watanabe, S., & Suzuki, A. 1992 Retrieval of faces from features described by eyewitnesses. Japanese Journal of Psychology, 63, 55-59.(In Japanese with English Summary)
Bruce, V., & Burton, M. 1989 Computer recognition of faces. In A. W. Young & H. B. Ellis (Eds.), Handbook of research on face processing. Amsterdam: North-Holland. pp.487-506.
Goldstein, A. J., Harmon, L.D., & Lesk, A. B. 1972 Man-machine interaction in human-face identification. Bell System Technical Journal, 51, 399-427.
Laughery, K. R., Rhodes, B. T., Jr. & Batten, G. W., Jr. 1981 Computer-guided recognition and retrieval of facial images. In G. Davies, H. Ellis & J. Shepherd (Eds.), Perceiving and remembering faces. London: Academic Press. pp.251-269.
Salton, G., & McGill, M. J. 1983 Introduction to modern information retrieval. New York: McGraw-Hill.
Shepherd, J. W. 1986 An interactive computer system for retrieving faces. In H. D. Ellis, M. A. Jeeves, F. Newcombe & A. Young (Eds), Aspects of face processing. Dordrecht: Martinus Nijhoff. pp.398-409.
Suzuki, A., Watanabe, S., & Adachi, K. 1991 Effects of reporting style, seeing condition and different target on retrieval accuracy. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 59-66.(In Japanese with English Summary)
Tversky, A. 1977 Features of similarity. Psychological Review, 84, 327-352.
Watanabe, S., Adachi, K., & Suzuki., A 1991 Retrieval of facial images using rating scales with standard stimuli. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 168-175.(In Japanese with English summary)

Date of correction: February 24, 2009 Reason for correction: - Correction: PDF FILE Details: -

Date of correction: February 24, 2009 Reason for correction: - Correction: ABSTRACT Details: Wrong : This paper presents a computer-based system for retrieving a witnessed face from a database of faces. To construct the database, a male adult was asked to observe 100 male adult faces one by one on a TV monitor and describe the features of each face using a set of 605 descriptors which had been collected in the previous study. Feature descriptors thus chosen for each face are stored in the database. A computer algorithm calculates a similarity value between a description by a witness and the stored description of each face, to search for the faces which match the witness's description The similarity is defined as a function of inter-feature similarities, using a vector representation of features. These inter-feature similarities are obtained from either human ratings or statistical correlations. An experimental evaluation of the system using 12 college students as “witnesses” gave promising results.
Right : This paper presents a computer-based system for retrieving a witnessed face from a database of faces. To construct the database, a male adult was asked to observe 100 male adult faces one by one on a TV monitor and describe the features of each face using a set of 605 descriptors which had been collected in the previous study. Feature descriptors thus chosen for each face are stored in the database. A computer algorithm calculates a similarity value between a description by a witness and the stored description of each face, to search for the faces which match the witness's description. The similarity is defined as a function of inter-feature similarities, using a vector representation of features. These inter-feature similarities are obtained from either human ratings or statistical correlations. An experimental evaluation of the system using 12 college students as “witnesses” gave promising results.

Date of correction: February 24, 2009 Reason for correction: - Correction: AFFILIATION Details: Wrong :
1) Notional Research Institute of Police Science

Right :
1) National Research Institute of Police Science

Date of correction: February 24, 2009 Reason for correction: - Correction: CITATION Details: Wrong : Adachi, K., Watanabe, S., & Suzuki, A. 1992 Retrieval of faces from features described by eyewitnesses. Japanese Journal of Psychology, 63, 55-59.(In Japanese with English Summary)
Bruce, V., & Burton, M. 1989 Computer recognition of faces. In A. W. Young & H. B. Ellis (Eds.), Handbook of research on face processing. Amsterdam: North-Holland. pp.487-506.
Goldstein, A. J., Harmon, L.D., & Lesk, A. B. 1972 Man-machine interaction in human-face identification. Bell System Technical Journal, 51, 399-427.
Laughery, K. R., Rhodes, B. T., Jr. & Batten, G. W., Jr. 1981 Computer-guided recognition and retrieval of facial images. In G. Davies, H. Ellis & J. Shepherd (Eds.), Perceiving and remembering faces. London: Academic Press. pp.251-269.
Salton, G., & McGill, M. J. 1983 Introduction to modern information retrieval. New York: McGraw-Hill.
Shepherd, J. W. 1986 An interactive computer system for retrieving faces. In H. D. Ellis, M. A. Jeeves, F. Newcombe & A. Young (Eds), Aspects of face processing. Dordrecht: Martinus Nijhoff. pp.398-409.
Suzuki, A., Watanabe, S., & Adachi, K. 1991 Effects of reporting style, seeing condition and different target on retrieval accuracy. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 59-66.(In Japanese with English Summary)
Tversky, A. 1977 Features of similarity. Psychological Review, 84, 327-352.
Watanabe, S., Adachi, K., & Suzuki., A 1991 Retrieval of facial images using rating scales with standard stimuli. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 168-175.(In Japanese with English summary)

Right : Adachi, K., Watanabe, S., & Suzuki, A. 1992 Retrieval of faces from features described by eyewitnesses. Japanese Journal of Psychology, 63, 55-59.(In Japanese with English Summary)
Bruce, V., & Burton, M. 1989 Computer recognition of faces. In A. W. Young & H. B. Ellis (Eds.), Handbook of research on face processing. Amsterdam: North-Holland. Pp.487-506.
Goldstein, A. J., Harmon, L. D., & Lesk, A. B. 1972 Man-machine interaction in human-face identification. Bell System Technical Journal, 51, 399-427.
Laughery, K. R., Rhodes, B. T., Jr. & Batten, G. W., Jr. 1981 Computer-guided recognition and retrieval of facial images. In G. Davies, H. Ellis & J. Shepherd (Eds.), Perceiving and remembering faces. London: Academic Press. Pp.251-269.
Salton, G., & McGill, M. J. 1983 Introduction to modern information retrieval. New York: McGraw-Hill.
Shepherd, J. W. 1986 An interactive computer system for retrieving faces. In H. D. Ellis, M. A. Jeeves, F. Newcombe & A. Young (Eds), Aspects of face processing. Dordrecht: Martinus Nijhoff. Pp.398-409.
Suzuki, A., Watanabe, S., & Adachi, K. 1991 Effects of reporting style, seeing condition and different target on retrieval accuracy. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 59-66.(In Japanese with English Summary)
Tversky, A. 1977 Features of similarity. Psychological Review, 84, 327-352.
Watanabe, S., Adachi, K., & Suzuki., A 1991 Retrieval of facial images using rating scales with standard stimuli. Reports of National Research Institute of Police Science, Research on Forensic Science, 44, 168-175.(In Japanese with English summary)

Abstract

This paper presents a computer-based system for retrieving a witnessed face from a database of faces. To construct the database, a male adult was asked to observe 100 male adult faces one by one on a TV monitor and describe the features of each face using a set of 605 descriptors which had been collected in the previous study. Feature descriptors thus chosen for each face are stored in the database. A computer algorithm calculates a similarity value between a description by a witness and the stored description of each face, to search for the faces which match the witness's description. The similarity is defined as a function of inter-feature similarities, using a vector representation of features. These inter-feature similarities are obtained from either human ratings or statistical correlations. An experimental evaluation of the system using 12 college students as “witnesses” gave promising results.

Corresponding author

Correction information

Register with J-STAGE for free!