Matching Forensic Sketches to Mug Shot Photos

The problem of matching a forensic sketch to a gallery of mug shot images is addressed in this paper. Previous research in sketch matching only offered solutions to matching highly accurate sketches that were drawn while looking at the subject (viewed sketches). Forensic sketches differ from viewed...

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Vydáno v:IEEE transactions on pattern analysis and machine intelligence Ročník 33; číslo 3; s. 639 - 646
Hlavní autoři: Klare, Brendan, Zhifeng Li, Jain, A K
Médium: Journal Article
Jazyk:angličtina
Vydáno: Los Alamitos, CA IEEE 01.03.2011
IEEE Computer Society
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Accuracy
Algorithms
Applied sciences
Artificial Intelligence
Biometry - methods
Computer science; control theory; systems
Discriminant analysis
Exact sciences and technology
Face
Face - anatomy & histology
Face recognition
Feature extraction
feature selection
Forensic engineering
Forensic Medicine - methods
forensic sketch
Forensics
Galleries
heterogeneous face recognition
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Intelligence
local feature discriminant analysis
Matching
Pattern analysis
Pattern Recognition, Automated - methods
Pattern recognition. Digital image processing. Computational geometry
Photography - methods
Principal component analysis
Reproducibility of Results
Shot
Sketches
Subtraction Technique
Training
viewed sketch
Discriminant analysis
Forensic science
Image processing
Face recognition
viewed sketch
local feature discriminant analysis
Sex
Pattern recognition
Multiscale method
heterogeneous face recognition
Facies
forensic sketch
Minimal distance
feature selection
ISSN:0162-8828, 1939-3539, 1939-3539
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Popis
Shrnutí:The problem of matching a forensic sketch to a gallery of mug shot images is addressed in this paper. Previous research in sketch matching only offered solutions to matching highly accurate sketches that were drawn while looking at the subject (viewed sketches). Forensic sketches differ from viewed sketches in that they are drawn by a police sketch artist using the description of the subject provided by an eyewitness. To identify forensic sketches, we present a framework called local feature-based discriminant analysis (LFDA). In LFDA, we individually represent both sketches and photos using SIFT feature descriptors and multiscale local binary patterns (MLBP). Multiple discriminant projections are then used on partitioned vectors of the feature-based representation for minimum distance matching. We apply this method to match a data set of 159 forensic sketches against a mug shot gallery containing 10,159 images. Compared to a leading commercial face recognition system, LFDA offers substantial improvements in matching forensic sketches to the corresponding face images. We were able to further improve the matching performance using race and gender information to reduce the target gallery size. Additional experiments demonstrate that the proposed framework leads to state-of-the-art accuracys when matching viewed sketches.
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ISSN:0162-8828
1939-3539
1939-3539
DOI:10.1109/TPAMI.2010.180