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Precise eye localization using HOG descriptors

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Precise eye localization using HOG descriptors

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dc.contributor.author Monzó Ferrer, David es_ES
dc.contributor.author Albiol Colomer, Alberto es_ES
dc.contributor.author Sastre, Jorge es_ES
dc.contributor.author Albiol Colomer, Antonio José es_ES
dc.date.accessioned 2015-12-14T12:44:01Z
dc.date.available 2015-12-14T12:44:01Z
dc.date.issued 2011-05
dc.identifier.issn 0932-8092
dc.identifier.uri http://hdl.handle.net/10251/58789
dc.description.abstract In this paper, we present a novel algorithm for precise eye detection. First, a couple of AdaBoost classifiers trained with Haar-like features are used to preselect possible eye locations. Then, a Support Vector Machine machine that uses Histograms of Oriented Gradients descriptors is used to obtain the best pair of eyes among all possible combinations of preselected eyes. Finally, we compare the eye detection results with three state-of-the-art works and a commercial software. The results show that our algorithm achieves the highest accuracy on the FERET and FRGCv1 databases, which is the most complete comparative presented so far. © Springer-Verlag 2010. es_ES
dc.description.sponsorship This work has been partially supported by the grant TEC2009-09146 of the Spanish Government. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Machine Vision and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject AdaBoost es_ES
dc.subject Eye detection es_ES
dc.subject HOG es_ES
dc.subject Local feature descriptors es_ES
dc.subject Commercial software es_ES
dc.subject Descriptors es_ES
dc.subject Eye localization es_ES
dc.subject Eye location es_ES
dc.subject Haar-like features es_ES
dc.subject Local feature es_ES
dc.subject Novel algorithm es_ES
dc.subject Pre-selected es_ES
dc.subject Algorithms es_ES
dc.subject Eye protection es_ES
dc.subject Adaptive boosting es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title Precise eye localization using HOG descriptors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00138-010-0273-0
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TEC2009-09146/ES/Nuevas Tecnicas Para Video Vigilancia Inteligente/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Monzó Ferrer, D.; Albiol Colomer, A.; Sastre, J.; Albiol Colomer, AJ. (2011). Precise eye localization using HOG descriptors. Machine Vision and Applications. 22(3):471-480. https://doi.org/10.1007/s00138-010-0273-0 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s00138-010-0273-0 es_ES
dc.description.upvformatpinicio 471 es_ES
dc.description.upvformatpfin 480 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 22 es_ES
dc.description.issue 3 es_ES
dc.relation.senia 216612 es_ES
dc.identifier.eissn 1432-1769
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.description.references Riopka, T., Boult, T.: The eyes have it. In: Proceedings of ACM SIGMM Multimedia Biometrics Methods and Applications Workshop, Berkeley, CA, pp. 9–16 (2003) es_ES
dc.description.references Kim C., Choi C.: Image covariance-based subspace method for face recognition. Pattern Recognit. 40(5), 1592–1604 (2007) es_ES
dc.description.references Wang, P., Green, M., Ji, Q., Wayman, J.: Automatic eye detection and its validation. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, vol. 3, San Diego, CA, pp. 164–171 (2005) es_ES
dc.description.references Amir A., Zimet L., Sangiovanni-Vincentelli A., Kao S.: An embedded system for an eye-detection sensor. Comput. Vis. Image Underst. 98(1), 104–123 (2005) es_ES
dc.description.references Zhu Z., Ji Q.: Robust real-time eye detection and tracking under variable lighting conditions and various face orientations. Comput. Vis. Image Underst. 98(1), 124–154 (2005) es_ES
dc.description.references Huang, W., Mariani, R.: Face detection and precise eyes location. In: Proceedings of the International Conference on Pattern Recognition, vol. 4, Washington, DC, USA, pp. 722–727 (2000) es_ES
dc.description.references Brunelli R., Poggio T.: Face recognition: features versus templates. IEEE Trans. Pattern Anal. Mach. Intell. 15(10), 1042–1052 (1993) es_ES
dc.description.references Guan, Y.: Robust eye detection from facial image based on multi-cue facial information. In: Proceedings of IEEE International Conference on Control and Automation, pp. 1775–1778 (2007) es_ES
dc.description.references Rizon, M., Kawaguchi, T.: Automatic eye detection using intensity and edge information. In: Proceedings of TENCON, vol. 2, Kuala Lumpur, Malaysia, pp. 415–420 (2000) es_ES
dc.description.references Han, C., Liao, H., Yu, K., Chen, L.: Fast face detection via morphology-based pre-processing. In: Proceedings of the 9th International Conference on Image Analysis and Processing, vol. 2. Springer, London, UK, pp. 469–476 (1997) es_ES
dc.description.references Song J., Chi Z., Liu J.: A robust eye detection method using combined binary edge and intensity information. Pattern Recognit. 39(6), 1110–1125 (2006) es_ES
dc.description.references Campadelli, P., Lanzarotti, R., Lipori, G.: Precise eye localization through a general-to-specific model definition. In: Proceedings of the British Machine Vision Conference, Edinburgh, Scotland, pp. 187–196 (2006) es_ES
dc.description.references Smeraldi F., Carmona O., Bign J.: Saccadic search with gabor features applied to eye detection and real-time head tracking. Image Vis. Comput. 18(4), 323–329 (1998) es_ES
dc.description.references Sirohey S. A., Rosenfeld A.: Eye detection in a face image using linear and nonlinear filters. Pattern Recognit. 34(7), 1367–1391 (2001) es_ES
dc.description.references Ma, Y., Ding, X., Wang, Z., Wang, N.: Robust precise eye location under probabilistic framework. In: Proceedings of the International Conference on Automatic Face and Gesture Recognition, Seoul, Korea, pp. 339–344 (2004) es_ES
dc.description.references Lu, H., Zhang, W., Yang D.: Eye detection based on rectangle features and pixel-pattern-based texture features. In: Proceedings of the International Symposium on Intelligent Signal Processing and Communication Systems, pp. 746–749 (2007) es_ES
dc.description.references Jin, L., Yuan, X., Satoh, S., Li, J., Xia, L.: A hybrid classifier for precise and robust eye detection. In: Proceedings of the International Conference on Pattern Recognition, vol. 4, Hong Kong, pp. 731–735 (2006) es_ES
dc.description.references Vapnik V. N.: The Nature of Statistical Learning Theory. Springer, New York Inc, New York, NY (1995) es_ES
dc.description.references Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, vol. 1, Hawaii, pp. 511–518 (2001) es_ES
dc.description.references Fasel I., Fortenberry B., Movellan J.: A generative framework for real time object detection and classification. Comput. Vis. Image Underst. 98(1), 182–210 (2005) es_ES
dc.description.references Huang J., Wechsler H.: Visual routines for eye location using learning and evolution. IEEE Trans. Evolut. Comput. 4(1), 73–82 (2000) es_ES
dc.description.references Behnke S.: Face localization and tracking in the neural abstraction pyramid. Neural Comput. Appl. 14(2), 97–103 (2005) es_ES
dc.description.references Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the 9th European Conference on Computer Vision, vol. 2, San Diego, CA, pp. 886–893 (2005) es_ES
dc.description.references Albiol A., Monzo D., Martin A., Sastre J., Albiol A.: Face recognition using hog-ebgm. Pattern Recognit. Lett. 29(10), 1537–1543 (2008) es_ES
dc.description.references Lowe D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004) es_ES
dc.description.references Bicego, M., Lagorio, A., Grosso, E., Tistarelli M.: On the use of SIFT features for face authentication. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition Workshop, New York, p. 35 (2006) es_ES
dc.description.references Yang M.-H., Kriegman D., Ahuja N.: Detecting faces in images: a survey. Trans. Pattern Anal. Mach. Intell. 24(1), 34–58 (2002) es_ES
dc.description.references Jain A., Murty M., Flynn P.: Data clustering: a review. ACM Comput. Syst. 31(3), 264–323 (1999) es_ES
dc.description.references Mikolajczyk K., Schmid C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005) es_ES
dc.description.references Humanscan, BioID database. http://www.bioid.com es_ES
dc.description.references Peer, P.: CVL Face database, University of Ljubjana. http://www.fri.uni-lj.si/en es_ES
dc.description.references Phillips P. J., Moon H., Rizvi S. A., Rauss P. J.: The feret evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090–1104 (2000) es_ES
dc.description.references Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Jin, C., Hoffman, K., Marques, J., Jaesik, M., Worek, W.: Overview of the face recognition grand challenge. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, vol. 1, San Diego, CA, pp. 947–954 (2005) es_ES
dc.description.references Jesorsky, O., Kirchberg, K.J., Frischholz, R.: Robust face detection using the hausdorff distance. In: Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication, Springer, London, UK, pp. 90–95 (2001) es_ES
dc.description.references Neurotechnologija, Biometrical and Artificial Intelligence Technologies, Verilook SDK. http://www.neurotechnologija.com es_ES
dc.description.references Witten I., Frank E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn: Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann, San Francisco (2005) es_ES
dc.description.references Turk M., Pentland A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991) es_ES


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