Faces are highly deformable objects which may easily change their appearance over time. Not all f... more Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore decoupling the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. This paper presents a robust face recognition technique based on the extraction and matching of SIFT features related to independent face areas. Both a global and local (as recognition from parts) matching strategy is proposed. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. In order to reduce the identification errors, the Dempster-Shafer decision theory is applied to fuse the two matching techniques. The proposed algorithms are evaluated with the ORL and the IITK face databases. The exp...
Guide to Biometric Reference Systems and Performance Evaluation, 2009
Abstract An overview of selected topics in face recognition is first presented in this chapter. T... more Abstract An overview of selected topics in face recognition is first presented in this chapter. The BioSecure 2D-face Benchmarking Framework is also described, com-posed of open-source software, publicly available databases and protocols. Three methods for 2D-face ...
Cancellable biometrics (CB) intentionally distorts biometric template for security protection, an... more Cancellable biometrics (CB) intentionally distorts biometric template for security protection, and simultaneously preserving the distance/similarity for matching in the transformed domain. Despite its effectiveness, the security issues attributed to similarity preservation property of CB is underestimated. Dong et al. [BTAS'19], exploited the similarity preservation trait of CB and proposed a similarity-based attack with high successful attack rate. The similarity-based attack utilizes preimage that generated from the protected biometric template for impersonation and perform cross matching. In this paper, we propose a constrained optimization similarity-based attack (CSA), which is improved upon Dong's genetic algorithm enabled similarity-based attack (GASA). The CSA applies algorithm-specific equality or inequality relations as constraints, to optimize preimage generation. We justify the effectiveness of CSA from the supervised learning perspective. We conduct extensive ex...
In the last decade deep learning techniques have strongly influenced many aspects of computationa... more In the last decade deep learning techniques have strongly influenced many aspects of computational vision. Many difficult vision tasks can now be performed by deploying a properly tailored and trained deep network. The enthusiasm for deep learning is unfortunately paired by the present lack of a clear understanding of how they work and why they provide such brilliant performance. The same applies to biometric systems. Deep learning has been successfully applied to several biometric recognition tasks, including face recognition. VGG-face is possibly the first deep convolutional network designed to perform face recognition, obtaining unsurpassed performance at the time it was firstly proposed. Over the last years, several and more complex deep convolutional networks, trained on very large, mainly private, datasets, have been proposed still elevating the performance bar also on quite challenging public databases, such as the Janus IJB-A and IJB-B. Despite of the progress in the develop...
Cancellable biometrics (CB) intentionally distorts biometric template for security protection, an... more Cancellable biometrics (CB) intentionally distorts biometric template for security protection, and simultaneously preserving the distance/similarity for matching in the transformed domain. Despite its effectiveness, the security issues attributed to similarity preservation property of CB is underestimated. Dong et al. [BTAS'19], exploited the similarity preservation trait of CB and proposed a similarity-based attack with high successful attack rate. The similarity-based attack utilizes preimage that generated from the protected biometric template for impersonation and perform cross matching. In this paper, we propose a constrained optimization similarity-based attack (CSA), which is improved upon Dong's genetic algorithm enabled similarity-based attack (GASA). The CSA applies algorithm-specific equality or inequality relations as constraints, to optimize preimage generation. We justify the effectiveness of CSA from the supervised learning perspective. We conduct extensive ex...
The editorial briefs the selected articles under the IEEE Access special section entitled “Visual... more The editorial briefs the selected articles under the IEEE Access special section entitled “Visual Surveillance and Biometrics: Practices, Challenges, and Possibilities”. INDEX TERMS Biometrics, Visual Surveillance, Forensics.
Recent research on face analysis has demonstrated the richness of information embedded in feature... more Recent research on face analysis has demonstrated the richness of information embedded in feature vectors extracted from a deep convolutional neural network. Even though deep learning achieved a very high performance on several challenging visual tasks, such as determining the identity, age, gender and race, it still lacks a well grounded theory which allows to properly understand the processes taking place inside the network layers. Therefore, most of the underlying processes are unknown and not easy to control. On the other hand, the human visual system follows a well understood process in analyzing a scene or an object, such as a face. The direction of the eye gaze is repeatedly directed, through purposively planned saccadic movements, towards salient regions to capture several details. In this paper we propose to capitalize on the knowledge of the saccadic human visual processes to design a system to predict facial attributes embedding a biologically-inspired network architectur...
One of the key factors to measure the progress of a research problem is the design of appropriate... more One of the key factors to measure the progress of a research problem is the design of appropriate evaluation protocols defined on suitable databases. Recently, the introduction of comprehensive databases and benchmarks of face videos has had a great impact on the development of new face recognition techniques. However, most of the protocols provided for these datasets are limited and do not capture requirements of unconstrained scenarios. That is why sometimes the performance of face recognition methods on current benchmarks seems to be saturated. To address this lack, the tendency is to collect new datasets, which is more expensive and sometimes the main the problem is not the data but the protocols. In this work, we propose new relevant evaluation protocols for the YouTube Faces database (REP-YTF) supporting face verification and open/closed-set identification. The proposal better fits realistic face recognition scenarios and allows us to test existing algorithms at relevant asses...
Biometrics has historically found its natural mate in Forensics. The first applications found in ... more Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Join...
The aim of this paper is to study the fusion at feature extraction level for face and fingerprint... more The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for concatenation. Moreover, to handle the 'problem of curse of dimensionality', the feature pointsets are properly reduced in dimension. Different feature reduction techniques are implemented, prior and after the feature pointsets fusion, and the results are duly recorded. The fused feature pointset for the database and the query face and fingerprint images are matched using techniques based on either the point pattern matching, or the Delaunay triangulation. Comparative experiments are conducted on chimeric and real databases, to assess the actual advantage of the fusion performed at the feature extraction level, in comparison to the matching score level.
Faces are highly deformable objects which may easily change their appearance over time. Not all f... more Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore decoupling the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. This paper presents a robust face recognition technique based on the extraction and matching of SIFT features related to independent face areas. Both a global and local (as recognition from parts) matching strategy is proposed. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. In order to reduce the identification errors, the Dempster-Shafer decision theory is applied to fuse the two matching techniques. The proposed algorithms are evaluated with the ORL and the IITK face databases. The exp...
Guide to Biometric Reference Systems and Performance Evaluation, 2009
Abstract An overview of selected topics in face recognition is first presented in this chapter. T... more Abstract An overview of selected topics in face recognition is first presented in this chapter. The BioSecure 2D-face Benchmarking Framework is also described, com-posed of open-source software, publicly available databases and protocols. Three methods for 2D-face ...
Cancellable biometrics (CB) intentionally distorts biometric template for security protection, an... more Cancellable biometrics (CB) intentionally distorts biometric template for security protection, and simultaneously preserving the distance/similarity for matching in the transformed domain. Despite its effectiveness, the security issues attributed to similarity preservation property of CB is underestimated. Dong et al. [BTAS'19], exploited the similarity preservation trait of CB and proposed a similarity-based attack with high successful attack rate. The similarity-based attack utilizes preimage that generated from the protected biometric template for impersonation and perform cross matching. In this paper, we propose a constrained optimization similarity-based attack (CSA), which is improved upon Dong's genetic algorithm enabled similarity-based attack (GASA). The CSA applies algorithm-specific equality or inequality relations as constraints, to optimize preimage generation. We justify the effectiveness of CSA from the supervised learning perspective. We conduct extensive ex...
In the last decade deep learning techniques have strongly influenced many aspects of computationa... more In the last decade deep learning techniques have strongly influenced many aspects of computational vision. Many difficult vision tasks can now be performed by deploying a properly tailored and trained deep network. The enthusiasm for deep learning is unfortunately paired by the present lack of a clear understanding of how they work and why they provide such brilliant performance. The same applies to biometric systems. Deep learning has been successfully applied to several biometric recognition tasks, including face recognition. VGG-face is possibly the first deep convolutional network designed to perform face recognition, obtaining unsurpassed performance at the time it was firstly proposed. Over the last years, several and more complex deep convolutional networks, trained on very large, mainly private, datasets, have been proposed still elevating the performance bar also on quite challenging public databases, such as the Janus IJB-A and IJB-B. Despite of the progress in the develop...
Cancellable biometrics (CB) intentionally distorts biometric template for security protection, an... more Cancellable biometrics (CB) intentionally distorts biometric template for security protection, and simultaneously preserving the distance/similarity for matching in the transformed domain. Despite its effectiveness, the security issues attributed to similarity preservation property of CB is underestimated. Dong et al. [BTAS'19], exploited the similarity preservation trait of CB and proposed a similarity-based attack with high successful attack rate. The similarity-based attack utilizes preimage that generated from the protected biometric template for impersonation and perform cross matching. In this paper, we propose a constrained optimization similarity-based attack (CSA), which is improved upon Dong's genetic algorithm enabled similarity-based attack (GASA). The CSA applies algorithm-specific equality or inequality relations as constraints, to optimize preimage generation. We justify the effectiveness of CSA from the supervised learning perspective. We conduct extensive ex...
The editorial briefs the selected articles under the IEEE Access special section entitled “Visual... more The editorial briefs the selected articles under the IEEE Access special section entitled “Visual Surveillance and Biometrics: Practices, Challenges, and Possibilities”. INDEX TERMS Biometrics, Visual Surveillance, Forensics.
Recent research on face analysis has demonstrated the richness of information embedded in feature... more Recent research on face analysis has demonstrated the richness of information embedded in feature vectors extracted from a deep convolutional neural network. Even though deep learning achieved a very high performance on several challenging visual tasks, such as determining the identity, age, gender and race, it still lacks a well grounded theory which allows to properly understand the processes taking place inside the network layers. Therefore, most of the underlying processes are unknown and not easy to control. On the other hand, the human visual system follows a well understood process in analyzing a scene or an object, such as a face. The direction of the eye gaze is repeatedly directed, through purposively planned saccadic movements, towards salient regions to capture several details. In this paper we propose to capitalize on the knowledge of the saccadic human visual processes to design a system to predict facial attributes embedding a biologically-inspired network architectur...
One of the key factors to measure the progress of a research problem is the design of appropriate... more One of the key factors to measure the progress of a research problem is the design of appropriate evaluation protocols defined on suitable databases. Recently, the introduction of comprehensive databases and benchmarks of face videos has had a great impact on the development of new face recognition techniques. However, most of the protocols provided for these datasets are limited and do not capture requirements of unconstrained scenarios. That is why sometimes the performance of face recognition methods on current benchmarks seems to be saturated. To address this lack, the tendency is to collect new datasets, which is more expensive and sometimes the main the problem is not the data but the protocols. In this work, we propose new relevant evaluation protocols for the YouTube Faces database (REP-YTF) supporting face verification and open/closed-set identification. The proposal better fits realistic face recognition scenarios and allows us to test existing algorithms at relevant asses...
Biometrics has historically found its natural mate in Forensics. The first applications found in ... more Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Join...
The aim of this paper is to study the fusion at feature extraction level for face and fingerprint... more The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for concatenation. Moreover, to handle the 'problem of curse of dimensionality', the feature pointsets are properly reduced in dimension. Different feature reduction techniques are implemented, prior and after the feature pointsets fusion, and the results are duly recorded. The fused feature pointset for the database and the query face and fingerprint images are matched using techniques based on either the point pattern matching, or the Delaunay triangulation. Comparative experiments are conducted on chimeric and real databases, to assess the actual advantage of the fusion performed at the feature extraction level, in comparison to the matching score level.
Uploads