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  • 1.
    Alonso-Fernandez, Fernando
    et al.
    ATVS/Biometric Recognition Group, Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Fierrez, Julian
    ATVS/Biometric Recognition Group, Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fronthaler, Hartwig
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Ortega-Garcia, Javier
    ATVS/Biometric Recognition Group, Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fingerprint Recognition2009Ingår i: Guide to Biometric Reference Systems and Performance Evaluation / [ed] Dijana Petrovska-Delacrétaz, Gérard Chollet, Bernadette Dorizzi, London: Springer London, 2009, s. 51-88Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    First, an overview of the state of the art in fingerprint recognition is presented, including current issues and challenges. Fingerprint databases and evaluation campaigns, are also summarized. This is followed by the description of the BioSecure Benchmarking Framework for Fingerprints, using the NIST Fingerpint Image Software (NFIS2), the publicly available MCYT-100 database, and two evaluation protocols. Two research systems are compared within the proposed framework. The evaluated systems follow different approaches for fingerprint processing and are discussed in detail. Fusion experiments involving different combinations of the presented systems are also given. The NFIS2 software is also used to obtain the fingerprint scores for the multimodal experiments conducted within the BioSecure Multimodal Evaluation Campaign(BMEC’2007) reported in Chap.11.

  • 2.
    Alonso-Fernandez, Fernando
    et al.
    University de Madrid, Madrid, Spain.
    Fierrez, J.
    Universidad Autonoma de Madrid.
    Ortega-Garcia, J.
    Universidad Autónoma de Madrid.
    Gonzalez-Rodriguez, J.
    Universidad Autónoma de Madrid.
    Fronthaler, Hartwig
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
    A Comparative Study of Fingerprint Image-Quality Estimation Methods2007Ingår i: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 2, nr 4, s. 734-743Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation. Poor-quality images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it is important for a fingerprint recognition system to estimate the quality and validity of the captured fingerprint images. In this work, we review existing approaches for fingerprint image-quality estimation, including the rationale behind the published measures and visual examples showing their behavior under different quality conditions. We have also tested a selection of fingerprint image-quality estimation algorithms. For the experiments, we employ the BioSec multimodal baseline corpus, which includes 19 200 fingerprint images from 200 individuals acquired in two sessions with three different sensors. The behavior of the selected quality measures is compared, showing high correlation between them in most cases. The effect of low-quality samples in the verification performance is also studied for a widely available minutiae-based fingerprint matching system.

  • 3.
    Alonso-Fernandez, Fernando
    et al.
    ATVS, Escuela Politecnica Superior, Campus de Cantoblanco, Avda. Francisco Tomas y Valiente 11, 28049 Madrid, Spain.
    Fierrez-Aguilar, Julian
    ATVS, Escuela Politecnica Superior, Campus de Cantoblanco, Avda. Francisco Tomas y Valiente 11, 28049 Madrid, Spain.
    Fronthaler, Hartwig
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Ortega-Garcia, Javier
    ATVS, Escuela Politecnica Superior, Campus de Cantoblanco, Avda. Francisco Tomas y Valiente 11, 28049 Madrid, Spain.
    Gonzalez-Rodriguez, Joaquin
    ATVS, Escuela Politecnica Superior, Campus de Cantoblanco, Avda. Francisco Tomas y Valiente 11, 28049 Madrid, Spain.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Combining multiple matchers for fingerprint verification: A case study in biosecure network of excellence2007Ingår i: Annales des télécommunications, ISSN 0003-4347, E-ISSN 1958-9395, Vol. 62, nr 1-2, s. 62-82Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We report on experiments for the fingerprint modality conducted during the First BioSecure Residential Workshop. Two reference systems for fingerprint verification have been tested together with two additional non-reference systems. These systems follow different approaches of fingerprint processing and are discussed in detail. Fusion experiments involving different combinations of the available systems are presented. The experimental results show that the best recognition strategy involves both minutiae-based and correlation-based measurements. Regarding the fusion experiments, the best relative improvement is obtained when fusing systems that are based on heterogeneous strategies for feature extraction and/or matching. The best combinations of two/three/four systems always include the best individual systems whereas the best verification performance is obtained when combining all the available systems.

  • 4.
    Bigun, Josef
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
    Fronthaler, Hartwig
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Assuring liveness in biometric identity authentication by real-time face tracking2004Ingår i: CIHSPS 2004: proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety : S. Giuliano, Venice, Italy, 21-22 July 2004 / [ed] IEEE, Piscataway, N.J.: IEEE Press, 2004, s. 104-111Konferensbidrag (Refereegranskat)
    Abstract [en]

    A system that combines real-time face tracking as well as the localization of facial landmarks in order to improve the authenticity of fingerprint recognition is introduced. The intended purpose of this application is to assist in securing public areas and individuals, in addition to enforce that the collected sensor data in a multi modal person authentication system originate front present persons, i.e. the system is not under a so called play back attack. Facial features are extracted with the help of Gabor filters and classified by SVM experts. For real-time performance, selected points from a retinotopic grid are used to form regional face models. Additionally only a subset of the Gabor decomposition is used for different face regions. The second modality presented is texture-based fingerprint recognition, exploiting linear symmetry. Experimental results on the proposed system are presented.

  • 5.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Automatic Image Quality Assessment with Application in Biometrics2006Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition / [ed] Cordelia Schmid, Stefano Soatto, Carlo Tomasi., Los Alamitos, Calif.: IEEE Computer Society, 2006, s. 7-Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method using local features to assess the quality of an image, with demonstration in biometrics, is proposed. Recently, image quality awareness has been found to increase recognition rates and to support decisions in multimodal authentication systems significantly. Nevertheless, automatic quality assessment is still an open issue, especially with regard to general tasks. Indicators of perceptual quality like noise, lack of structure, blur, etc. can be retrieved from the orientation tensor of an image, but there are few studies reporting on this. Here we study the orientation tensor with a set of symmetry descriptors, which can be varied according to the application. Allowed classes of local shapes are generically provided by the user but no training or explicit reference information is required. Experimental results are given for fingerprint. Furthermore, we indicate the applicability of the proposed method to face images.

  • 6.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Local feature extraction in fingerprints by complex filtering2005Ingår i: Advances in Biometric Person Authentication International Wokshop on Biometric Recognition Systems, IWBRS 2005, Beijing, China, October 22-23, 2005. Proceedings / [ed] Stan Z. Li, Zhenan Sun, Tieniu Tan, Sharath Pankanti, Gérard Chollet and David Zhang, Berlin: Springer Berlin/Heidelberg, 2005, s. 77-84Konferensbidrag (Refereegranskat)
    Abstract [en]

    A set of local feature descriptors for fingerprints is proposed. Minutia points are detected in a novel way by complex filtering of the structure tensor, not only revealing their position but also their direction. Parabolic and linear symmetry descriptions are used to model and extract local features including ridge orientation and reliability, which can be reused in several stages of fingerprint processing. Experimental results on the proposed technique are presented.

  • 7.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Local Features for Enhancement and Minutiae Extraction in Fingerprints2008Ingår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 17, nr 3, s. 354-363Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Accurate fingerprint recognition presupposes robust feature extraction which is often hampered by noisy input data. We suggest common techniques for both enhancement and minutiae extraction, employing symmetry features. For enhancement, a Laplacian-like image pyramid is used to decompose the original fingerprint into sub-bands corresponding to different spatial scales. In a further step, contextual smoothing is performed on these pyramid levels, where the corresponding filtering directions stem from the frequency-adapted structure tensor (linear symmetry features). For minutiae extraction, parabolic symmetry is added to the local fingerprint model which allows to accurately detect the position and direction of a minutia simultaneously. Our experiments support the view that using the suggested parabolic symmetry features, the extraction of which does not require explicit thinning or other morphological operations, constitute a robust alternative to conventional minutiae extraction. All necessary image processing is done in the spatial domain using 1-D filters only, avoiding block artifacts that reduce the biometric information. We present comparisons to other studies on enhancement in matching tasks employing the open source matcher from NIST, FIS2. Furthermore, we compare the proposed minutiae extraction method with the corresponding method from the NIST package, mindtct. A top five commercial matcher from FVC2006 is used in enhancement quantification as well. The matching error is lowered significantly when plugging in the suggested methods. The FVC2004 fingerprint database, notable for its exceptionally low-quality fingerprints, is used for all experiments.

  • 8.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Pyramid-based Image Enhancement of Fingerprints2007Ingår i: 2007 IEEE Workshop on Automatic Identification Advanced Technologies proceedings : 7-8 June 2007, Alghero, Italy, Piscataway, NJ.: IEEE Press, 2007, s. 45-50Konferensbidrag (Refereegranskat)
    Abstract [en]

    Reliable feature extraction is crucial for accurate biometric recognition. Unfortunately feature extraction is hampered by noisy input data, especially so in case of fingerprints. We propose a method to enhance the quality of a given fingerprint with the purpose to improve the recognition performance. A Laplacian like image-scale pyramid is used for this purpose to decompose the original fingerprint into 3 smaller images corresponding to different frequency bands. In a further step, contextual filtering is performed using these pyramid levels and 1D Gaussians, where the corresponding filtering directions are derived from the frequency-adapted structure tensor. All image processing is done in the spatial domain, avoiding block artifacts while conserving the biometric signal well. We report on comparative results and present quantitative improvements, by applying the standardized NIST FIS2 fingerprint matcher to the FVC2004 fingerprint database along with our as well as two other enhancements. The study confirms that the suggested enhancement robustifies feature detection, e.g. minutiae, which in turn improves the recognition (20% relative improvement in equal error rate on DB3 of FVC2004).

  • 9.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Fierrez, Julian
    Univ Autonoma Madrid, Escuela Politec Super, ATVS, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Univ Autonoma Madrid, Escuela Politec Super, ATVS, Madrid, Spain.
    Ortega-Garcia, Javier
    Univ Autonoma Madrid, Escuela Politec Super, ATVS, Madrid, Spain.
    Gonzalez-Rodriguez, Joaquin
    Univ Autonoma Madrid, Escuela Politec Super, ATVS, Madrid, Spain.
    Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification2008Ingår i: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 3, nr 2, s. 331-338Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Signal-quality awareness has been found to increase recognition rates and to support decisions in multisensor environments significantly. Nevertheless, automatic quality assessment is still an open issue. Here, we study the orientation tensor of fingerprint images to quantify signal impairments, such as noise, lack of structure, blur, with the help of symmetry descriptors. A strongly reduced reference is especially favorable in biometrics, but less information is not sufficient for the approach. This is also supported by numerous experiments involving a simpler quality estimator, a trained method (NFIQ), as well as the human perception of fingerprint quality on several public databases. Furthermore, quality measurements are extensively reused to adapt fusion parameters in a monomodal multialgorithm fingerprint recognition environment. In this study, several trained and nontrained score-level fusion schemes are investigated. A Bayes-based strategy for incorporating experts' past performances and current quality conditions, a novel cascaded scheme for computational efficiency, besides simple fusion rules, is presented. The quantitative results favor quality awareness under all aspects, boosting recognition rates and fusing differently skilled experts efficiently as well as effectively (by training).

  • 10.
    Fronthaler, Hartwig
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Kollreider, Klaus
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Fierrez-Aguilar, Julian
    Universidad Autonoma de Madrid.
    Alonso-Fernandez, Fernando
    Universidad Autonoma de Madrid.
    Ortega-Garcia, Javier
    Universidad Autonoma de Madrid.
    Gonzalez-Rodriguez, Joaquin
    Universidad Autonoma de Madrid.
    Fingerprint Image Quality Estimation and its Application to Multi-Algorithm Verification2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Recently, image quality awareness has been found to increase recognition rates and to supportdecisions in multimodal authentication systems significantly. Nevertheless, automatic quality assessmentis still an open issue, especially with regard to biometric authentication tasks. Here we analyze theorientation tensor of fingerprint images with a set of symmetry descriptors, in order to detect fingerprintimage quality impairments like noise, lack of structure, blur, etc. Allowed classes of local shapes area priori application information for the proposed quality measures, therefore no training or explicitimage reference information is required. Our quality assessment method is compared to an existingautomatic method and a human opinion in numerous experiments involving several public databases.Once the quality of an image is determined, it can be exploited in several ways, one of which is toadapt fusion parameters in a monomodal multi-algorithm environment, here a number of fingerprintrecognition systems. In this work, several trained and non-trained fusion schemes applied to the scoresof these matchers are compared. A Bayes-based strategy for combining experts with weights on theirpast performances, able to readapt to each identity claim based on the input quality is developed andevaluated. To show some of the advantages of quality-driven multi-algorithm fusion, such as boostingrecognition rates, increasing computational efficiency, etc., a novel cascade fusion and simple fusionrules are employed in comparison as well.

  • 11.
    Kollreider, Klaus
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Fronthaler, Hartwig
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Evaluating liveness by face images and the structure tensor2005Ingår i: Proceedings - Fourth IEEE Workshop on Automatic Identification Advanced Technologies, 2005, New York: IEEE Press, 2005, s. 75-80Konferensbidrag (Refereegranskat)
    Abstract [en]

    A technique evaluating liveness in short face image sequences is presented The intended purpose of the proposed system is to assist in a biometric authentication framework, by adding liveness awareness in a non-intrusive manner. Analyzing the trajectories of single parts of a live face reveal valuable information to discriminate it against a spoofed one. The proposed system uses a lightweight novel optical flow, which is especially applicable in face motion estimation based on the structure tensor and a few frames. It uses a model-based local Gabor decomposition and SVM experts for face part detection. An alternative approach for face pan detection using optical flow pattern matching is introduced as well. Experimental results on the proposed system are presented.

  • 12.
    Kollreider, Klaus
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Fronthaler, Hartwig
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
    Non-intrusive liveness detection by face images2009Ingår i: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 27, nr 3, s. 233-244Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A technique evaluating liveness in face image sequences is presented. To ensure the actual presence of a live face in contrast to a photograph (playback attack), is a significant problem in face authentication to the extent that anti-spoofing measures are highly desirable. The purpose of the proposed system is to assist in a biometric authentication framework, by adding liveness awareness in a non-intrusive manner. Analyzing the trajectories of certain parts of a live face reveals valuable information to discriminate it against a spoofed one. The proposed system uses a lightweight novel optical flow, which is especially applicable in face motion estimation based on the structure tensor and inputs of a few frames. For reliable face part detection, the system utilizes a model-based local Gabor decomposition and SVM experts, where selected points from a retinotopic grid are used to form regional face models. Also the estimated optical flow is exploited to detect a face part. The whole procedure, starting with three images as input and finishing in a liveness score, is executed in near real-time without special purpose hardware. Experimental results on the proposed system are presented on both a public database and spoofing attack simulations.

  • 13.
    Kollreider, Klaus
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Fronthaler, Hartwig
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Verifying Liveness by Multiple Experts in Face Biometrics2008Ingår i: IEEE Conference on Computer Vision and Pattern Recognition Workshops: CVPR 2008, Anchorage, Alaska, June 23-28, 2008, New York: IEEE Press, 2008, s. 1200-1205Konferensbidrag (Refereegranskat)
    Abstract [en]

    Resisting spoofing attempts via photographs and video playbacks is a vital issue for the success of face biometrics. Yet, the “liveness ” topic has only been partially studied in the past. In this paper we are suggesting a holistic liveness detection paradigm that collaborates with standard techniques in 2D face biometrics. The experiments show that many attacks are avertible via a combination of antispoofing measures. We have investigated the topic using real-time techniques and applied them to real-life spoofing scenarios in an indoor, yet uncontrolled environment.

  • 14.
    Kollreider, Klaus
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Fronthaler, Hartwig
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Faraj, Maycel
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment2007Ingår i: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 2, nr 3 part 2, s. 548-558Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A robust face detection technique along with mouth localization, processing every frame in real time (video rate), is presented. Moreover, it is exploited for motion analysis onsite to verify "liveness" as well as to achieve lip reading of digits. A methodological novelty is the suggested quantized angle features ("quangles") being designed for illumination invariance without the need for preprocessing (e.g., histogram equalization). This is achieved by using both the gradient direction and the double angle direction (the structure tensor angle), and by ignoring the magnitude of the gradient. Boosting techniques are applied in a quantized feature space. A major benefit is reduced processing time (i.e., that the training of effective cascaded classifiers is feasible in very short time, less than 1 h for data sets of order 104). Scale invariance is implemented through the use of an image scale pyramid. We propose "liveness" verification barriers as applications for which a significant amount of computation is avoided when estimating motion. Novel strategies to avert advanced spoofing attempts (e.g., replayed videos which include person utterances) are demonstrated. We present favorable results on face detection for the YALE face test set and competitive results for the CMU-MIT frontal face test set as well as on "liveness" verification barriers.

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