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 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 s...

• Type: Journal
• Year: 2011
• Where: PAMI
• Authors: Brendan Klare, Zhifeng Li, Anil K. Jain
• Keywords: Accurate Sketches, Feature-based Discriminant Analysis, Forensic Sketches, Operations Research, PAMI 2011