An Experiment on Human Face Recognition Performance for Access Control

Butavicius, Marcus A.; Mount, Chloë; MacLeod, Veneta; Vast, Robyn; Graves, I.; Sunde, Jadranka

doi:10.1007/978-3-540-85563-7_23

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…The issues with forensic science raised by Kassin, Dror, and Kukucka (2013) equally apply to facial image comparison. Ground truth is often not known (Phillips, 2011), objective standards are still in the development phase (FISWG, 2012a), previous empirical studies have confirmed inter-variations (Butavicius et al, 2008; Megreya & Burton, 2006, 2007, 2008) and intra-variations in performance (Bindemann, Avetisyan, & Rakow, 2012), and the quantification of a match is not currently possible as there is no statistical basis for doing so (Mallett, Dryden, Vorder Bruegge, & Evison, 2010; Spaun & Vorder Bruegge, 2008).…”

Section: Issues With Facial Image Comparisonmentioning

confidence: 99%

Forensic confirmation bias: The case of facial image comparison.

Heyer

Semmler

2013

Journal of Applied Research in Memory and Cognition

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Section: Issues With Facial Image Comparisonmentioning

confidence: 99%

Forensic confirmation bias: The case of facial image comparison.

Heyer

Semmler

2013

Journal of Applied Research in Memory and Cognition

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“…Face recognition has been used in different fields of security and protection, namely automated crowd surveillance [39], access control [6], identification of convicts [40], face reconstruction [43,44,45] and so on. Thus, it has been one of the challenging issues in the last decade and it is a necessity in our current life.…”

Section: Face Recognitionmentioning

confidence: 99%

“…Currently, due to the increment of violence and crime rate, the usage of systems to establish security and safety is a critical requirement to the current human's life [1]. To deal with this requirement, face recognition of convicts is considered as the major purpose in development of such systems [6]. In addition, since the events of September 11, the process of development and implementation of automated biometric systems have been noticeably increased [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…To deal with this requirement, face recognition of convicts is considered as the major purpose in development of such systems [6]. In addition, since the events of September 11, the process of development and implementation of automated biometric systems have been noticeably increased [6,7]. Moreover, there are many practical situations in which we need to the techniques of pattern recognition, and in particular face recognition.…”

Section: Introductionmentioning

confidence: 99%

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Experiments with Face Recognition Using a Novel Approach Based on CVQ Technique

Mehrbakhsh

Khalilian

2012

IFIP Advances in Information and Communication Technology

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Face recognition techniques attempt to identify faces according to the patterns of mouth, lip, eyes and so on. However, the effectiveness of existing approaches degrades in presence of uncontrolled conditions such as variations of background light and image sizes. To deal with this problem, we propose a novel approach based on Classified Vector Quantization (CVQ) technique. The new approach divides images into some blocks and each block is classified into several patterns. Then, the Vector Quantization (VQ) technique is applied on the vectors of each pattern. In order to evaluate our approach, we have conducted a family of experiments on some standard image databases, MIT, YALE, and AR. The results demonstrate that the new approach is steadily capable of identifying faces in different situations.

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“…According to this requirement, face recognition of convicts can be considered as the main purpose in implementation of these systems. In addition, since the events of September 11, the process of development and implementation of automated biometric solutions have been accelerated [7], [8].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach Based on CVQ Technique for Face Recognition

Mehrbakhsh¹,

Khalilian²

2012

IJCEE

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Face recognition has been widely used to identify faces according to the patterns of mouth, lip, eyes and so on. Existing face recognition techniques provide a reasonable accuracy. However, their effectiveness significantly degrades in presence of uncontrolled conditions such as variations of background light and image sizes. To deal with this problem, we propose a novel approach based on Classified Vector Quantization (CVQ) technique for face recognition. The new approach divides images into some blocks and each block is classified into several patterns. The Vector Quantization technique (VQ) is applied on the vectors of each pattern. A major benefit of this technique is to consider the geometric structure of face and skin correlations which provide recognition based on changes on human's age. In order to evaluate our approach, experiments on some standard image databases have been conducted. The results demonstrate the high recognition rate and accuracy of our technique.

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An Experiment on Human Face Recognition Performance for Access Control

Cited by 4 publications

References 7 publications

Forensic confirmation bias: The case of facial image comparison.

Forensic confirmation bias: The case of facial image comparison.

Experiments with Face Recognition Using a Novel Approach Based on CVQ Technique

A Novel Approach Based on CVQ Technique for Face Recognition

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