Human Face Image Searching System Using Sketches

Yuen, Pong C.; Man, Chuntao

doi:10.1109/tsmca.2007.897588

Cited by 49 publications

(36 citation statements)

References 10 publications

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“…The naming conventions have been corrected in this study to reflect the prevailing law enforcement terminology. While several methods that match viewed 4 and hand-drawn composites to mugshots have been reported in the literature [7], [8], [11], [16], [10], [15], [14], [18], only a few methods have been published for automatic matching of softwaregenerated composites to mugshots [16], [17]. In all the previous studies reported on software-generated composites, with the exception of [6], composites were created while the operator was viewing the high quality mugshot.…”

mentioning

confidence: 99%

The FaceSketchID System: Matching Facial Composites to Mugshots

Klum

Han

Klare

et al. 2014

IEEE Trans.Inform.Forensic Secur.

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Abstract-Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. These composites, generated from witness descriptions, are posted in public places and in the media with the hope that some viewers will provide tips about the identity of the suspect. This method of identifying suspects is slow, tedious, and may not lead to the timely apprehension of a suspect. Hence, there is a need for a method that can automatically and efficiently match facial composites to large police mugshot databases. Because of this requirement, facial composite recognition is an important topic for biometrics researchers. While substantial progress has been made in nonforensic facial composite (or viewed composite) recognition over the past decade, very little work has been done using operational composites relevant to law enforcement agencies. Furthermore, no facial composite to mugshot matching systems have been documented that are readily deployable as standalone software. Thus, the contributions of this paper include: (i) an exploration of composite recognition use cases involving multiple forms of facial composites, (ii) the FaceSketchID System, a scalable and operationally deployable software system that achieves stateof-the-art matching accuracy on facial composites using two algorithms (holistic and component-based), and (iii) a study of the effects of training data on algorithm performance. We present experimental results using a large mugshot gallery that is representative of a law enforcement agency's mugshot database. All results are compared against three state-of-the-art commercial-off-the-shelf (COTS) face recognition systems.

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mentioning

confidence: 99%

The FaceSketchID System: Matching Facial Composites to Mugshots

Klum

Han

Klare

et al. 2014

IEEE Trans.Inform.Forensic Secur.

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“…Klare and Jain [9] SIFT and MBLP feature descriptors with local-feature based discriminant analysis Bhatt et al [18] Multi-scale circular Weber's local descriptor Composite Yuen and Man [7] Point distribution model and geometrical relationship Composite sketches were created while viewing the photograph. Forensic sketches were not considered.…”

Section: Forensicmentioning

confidence: 99%

“…However, matching facial sketches to photographs is a more challenging problem with only a limited amount of published work [4,5,6,7,8,9,10,11]. Of these, most studies have used viewed sketches drawn while viewing the mugshot photograph.…”

Section: Related Workmentioning

confidence: 99%

“…The first used a combination of local and global features to represent sketches [7], but it required user input in the form of relevance feedback in the matching or recognition phase. Further, the authors in [7] used a small gallery in their experiments (300 facial photographs). The method proposed by Han et al [11], used a component based approach to match facial sketches to mugshots.…”

Section: Related Workmentioning

confidence: 99%

“…While several methods that match viewed 3 and forensic sketches to mugshots have been reported in the literature [4,5,6,7,8,9,10], far fewer methods exist for automatic matching of composite sketches to mugshots [7,11]. In all the previous studies reported on composite sketches, sketches were created while the operator was viewing the mugshot.…”

Section: Introductionmentioning

confidence: 99%

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Sketch based face recognition: Forensic vs. composite sketches

Klum

Han

Jain

et al. 2013

2013 International Conference on Biometrics (ICB)

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Facial sketches are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. Sketches used in forensic investigations are either drawn by forensic artists (forensic sketches) or created with computer software (composite sketches) following the verbal description provided by an eyewitness or the victim. These sketches are posted in public places and in media in hopes that some viewers will provide tips about the identity of the suspect. This method of identifying suspects is slow and tedious and may not lead to apprehension of the suspect. Hence, there is a need for a method that can automatically and quickly match facial sketches to large police mugshot databases. We address the problem of automatic facial sketch to mugshot matching and, for the first time, compare the effectiveness of forensic sketches and composite sketches. The contributions of this paper include: (i) a database containing mugshots and corresponding forensic and composite sketches that will be made available to interested researchers; (ii) a comparison of holistic facial representations versus component based representations for sketch to mugshot matching; and (iii) an analysis of the effect of filtering a mugshot gallery using three sources of demographic information (age, gender and race/ethnicity). Our experimental results show that composite sketches are matched with higher accuracy than forensic sketches to the corresponding mugshots. Both of the face representations studied here yield higher sketch to photo matching accuracy compared to a commercial face matcher.

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