Littérature scientifique sur le sujet « Unconstrained face recognition »
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Articles de revues sur le sujet "Unconstrained face recognition"
Deng, Weihong, Jiani Hu, Zhongjun Wu et Jun Guo. « Lighting-aware face frontalization for unconstrained face recognition ». Pattern Recognition 68 (août 2017) : 260–71. http://dx.doi.org/10.1016/j.patcog.2017.03.024.
Texte intégralMasi, Iacopo, Anh Tuấn Trần, Tal Hassner, Gozde Sahin et Gérard Medioni. « Face-Specific Data Augmentation for Unconstrained Face Recognition ». International Journal of Computer Vision 127, no 6-7 (1 avril 2019) : 642–67. http://dx.doi.org/10.1007/s11263-019-01178-0.
Texte intégralTyagi, Ranbeer, Geetam Singh Tomar et Laxmi Shrivastava. « Unconstrained Face Recognition Quality : A Review ». International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no 11 (30 novembre 2016) : 199–210. http://dx.doi.org/10.14257/ijsip.2016.9.11.18.
Texte intégralVinay, A., Abhijay Gupta, Aprameya Bharadwaj, Arvind Srinivasan, K. N. Balasubramanya Murthy et S. Natarajan. « Unconstrained Face Recognition using Bayesian Classification ». Procedia Computer Science 143 (2018) : 519–27. http://dx.doi.org/10.1016/j.procs.2018.10.425.
Texte intégralRifaee, Mustafa, Mohammad Al Rawajbeh, Basem AlOkosh et Farhan AbdelFattah. « A New approach to Recognize Human Face Under Unconstrained Environment ». International Journal of Advances in Soft Computing and its Applications 14, no 2 (20 juillet 2022) : 2–13. http://dx.doi.org/10.15849/ijasca.220720.01.
Texte intégralYu, Aihua, Gang Li, Beiping Hou, Hongan Wang et Gaoya Zhou. « A novel framework for face recognition using robust local representation–based classification ». International Journal of Distributed Sensor Networks 15, no 3 (mars 2019) : 155014771983608. http://dx.doi.org/10.1177/1550147719836082.
Texte intégralTORBATI, Ali, et Önsen TOYGAR. « MASKED AND UNMASKED FACE RECOGNITION ON UNCONSTRAINED FACIAL IMAGES USING HAND-CRAFTED METHODS ». Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 26, Özel Sayı (12 décembre 2023) : 1133–39. http://dx.doi.org/10.17780/ksujes.1339868.
Texte intégralRuan, Shuai, Chaowei Tang, Xu Zhou, Zhuoyi Jin, Shiyu Chen, Haotian Wen, Hongbin Liu et Dong Tang. « Multi-Pose Face Recognition Based on Deep Learning in Unconstrained Scene ». Applied Sciences 10, no 13 (7 juillet 2020) : 4669. http://dx.doi.org/10.3390/app10134669.
Texte intégralTong, Ying, Jiachao Zhang et Rui Chen. « Discriminative Sparsity Graph Embedding for Unconstrained Face Recognition ». Electronics 8, no 5 (7 mai 2019) : 503. http://dx.doi.org/10.3390/electronics8050503.
Texte intégralAgrawal, Amrit Kumar, et Yogendra Narain Singh. « Unconstrained face recognition using deep convolution neural network ». International Journal of Information and Computer Security 12, no 2/3 (2020) : 332. http://dx.doi.org/10.1504/ijics.2020.10026788.
Texte intégralThèses sur le sujet "Unconstrained face recognition"
Zhou, Shaohua. « Unconstrained face recognition ». College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1800.
Texte intégralThesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Wei, Xingjie. « Unconstrained face recognition with occlusions ». Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66778/.
Texte intégralJuefei-Xu, Felix. « Unconstrained Periocular Face Recognition : From Reconstructive Dictionary Learning to Generative Deep Learning and Beyond ». Research Showcase @ CMU, 2018. http://repository.cmu.edu/dissertations/1189.
Texte intégralLopes, Daniel Pedro Ferreira. « Face verication for an access control system in unconstrained environment ». Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23395.
Texte intégralO reconhecimento facial tem vindo a receber bastante atenção ao longo dos últimos anos não só na comunidade cientifica, como também no ramo comercial. Uma das suas várias aplicações e o seu uso num controlo de acessos onde um indivíduo tem uma ou várias fotos associadas a um documento de identificação (também conhecido como verificação de identidade). Embora atualmente o estado da arte apresente muitos estudos em que tanto apresentam novos algoritmos de reconhecimento como melhorias aos já desenvolvidos, existem mesmo assim muitos problemas ligados a ambientes não controlados, a aquisição de imagem e a escolha dos algoritmos de deteção e de reconhecimento mais eficazes. Esta tese aborda um ambiente desafiador para a verificação facial: um cenário não controlado para o acesso a infraestruturas desportivas. Uma vez que não existem condições de iluminação controladas nem plano de fundo controlado, isto torna um cenário complicado para a implementação de um sistema de verificação facial. Esta tese apresenta um estudo sobre os mais importantes algoritmos de detecção e reconhecimento facial assim como técnicas de pré-processamento tais como o alinhamento facial, a igualização de histograma, com o objetivo de melhorar a performance dos mesmos. Também em são apresentados dois métodos para a aquisição de imagens envolvendo a seleção de imagens e calibração da câmara. São apresentados resultados experimentais detalhados baseados em duas bases de dados criadas especificamente para este estudo. No uso de técnicas de pré-processamento apresentadas, foi possível presenciar melhorias até 20% do desempenho dos algoritmos de reconhecimento referentes a verificação de identidade. Com os métodos apresentados para os testes ao ar livre, foram conseguidas melhorias na ordem dos 30%.
Face Recognition has been received great attention over the last years, not only on the research community, but also on the commercial side. One of the many uses of face recognition is its use on access control systems where a person has one or several photos associated to an Identi cation Document (also known as identity veri cation). Although there are many studies nowadays, both presenting new algorithms or just improvements of the already developed ones, there are still many open problems regarding face recognition in uncontrolled environments, from the image acquisition conditions to the choice of the most e ective detection and recognition algorithms, just to name a few. This thesis addresses a challenging environment for face veri cation: an unconstrained environment for sports infrastructures access. As there are no controlled lightning conditions nor controlled background, this makes a di cult scenario to implement a face veri cation system. This thesis presents a study of some of the most important facial detection and recognition algorithms as well as some pre-processing techniques, such as face alignment and histogram equalization, with the aim to improve their performance. It also introduces some methods for a more e cient image acquisition based on image selection and camera calibration, specially designed for addressing this problem. Detailed experimental results are presented based on two new databases created speci cally for this study. Using pre-processing techniques, it was possible to improve the recognition algorithms performances up to 20% regarding veri cation results. With the methods presented for the outdoor tests, performances had improvements up to 30%
Stone, Zachary. « Face Identification in the Internet Era ». Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10397.
Texte intégralEngineering and Applied Sciences
Vu, Ngoc-Son. « Contributions à la reconnaissance de visages à partir d'une seule image et dans un contexte non-contrôlé ». Phd thesis, Grenoble INPG, 2010. https://theses.hal.science/tel-00574547v1.
Texte intégralAlthough having been an active research topic for 30 years, recognizing a person from surveillance having seen only one image is unsolved. Within this context, the two greatest challenges are the variations of pose and illumination. Moreover, there are strict constraints upon the complexity in both terms of computational time and stockage requirements. The work developed throughout this dissertation gives several advantages in the context of real-time and unconstrained face recognition. Firstly, an illumination normalization method simulating the performance of human retina is proposed as preprocessing algorithm. Secondly, we propose novel features called POEM (Patterns of Oriented Edge Magnitudes) for representing a local image structure. This descriptor is discriminative and robust to exterior variations (variations of pose, illumination, expression and pose that we always see when dealing with face images). Thirdly, a statistical model for robust face recognition across poses, entered on modeling how facial patch appearance changes as the viewpoint varies, is proposed. Finally, a novel approach modeling the spatial relationships between face components is developed. Except the last algorithm, all proposed methods are very fast and are therefore suitable for the constraints upon real-time of surveillance applications
Mudunuri, Sivaram Prasad. « Face Recognition in Unconstrained Environment ». Thesis, 2019. https://etd.iisc.ac.in/handle/2005/5113.
Texte intégralReigoto, Anabela Machado. « Face Detection and Recognition in Unconstrained Scenarios ». Master's thesis, 2019. https://hdl.handle.net/10216/122842.
Texte intégralSanyal, Soubhik. « Discriminative Descriptors for Unconstrained Face and Object Recognition ». Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4177.
Texte intégralFreitas, Tiago Daniel Santos. « 3D Face Recognition Under Unconstrained settings using Low-Cost Sensors ». Master's thesis, 2016. https://repositorio-aberto.up.pt/handle/10216/84513.
Texte intégralLivres sur le sujet "Unconstrained face recognition"
Unconstrained Face Recognition. Springer US, 2006. http://dx.doi.org/10.1007/978-0-387-29486-5.
Texte intégralChellappa, Rama, Shaohua Kevin Zhou et Wenyi Zhao. Unconstrained Face Recognition. Springer, 2010.
Trouver le texte intégralUnconstrained Face Recognition (International Series on Biometrics). Springer, 2005.
Trouver le texte intégralChellappa, Rama, Shaohua Kevin Zhou et Wenyi Zhao. Unconstrained Face Recognition (International Series on Biometrics Book 5). Springer, 2006.
Trouver le texte intégralChapitres de livres sur le sujet "Unconstrained face recognition"
Ouanan, Hamid, Mohammed Ouanan et Brahim Aksasse. « Myface : Unconstrained Face Recognition ». Dans Lecture Notes in Networks and Systems, 86–94. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69137-4_9.
Texte intégralKocjan, Przemysław, et Khalid Saeed. « Face Recognition in Unconstrained Environment ». Dans Biometrics and Kansei Engineering, 21–42. New York, NY : Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5608-7_2.
Texte intégralGong, Xun, Jun Luo et Zehua Fu. « Normalization for Unconstrained Pose-Invariant 3D Face Recognition ». Dans Biometric Recognition, 1–8. Cham : Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02961-0_1.
Texte intégralLiu, Feng, Minchul Kim, Anil Jain et Xiaoming Liu. « Controllable and Guided Face Synthesis for Unconstrained Face Recognition ». Dans Lecture Notes in Computer Science, 701–19. Cham : Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19775-8_41.
Texte intégralWu, Zhongjun, Weihong Deng et Zhanfu An. « Illumination-Recovered Pose Normalization for Unconstrained Face Recognition ». Dans Computer Vision – ACCV 2016, 217–33. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54187-7_15.
Texte intégralTome, Pedro, Ruben Vera-Rodriguez, Julian Fierrez et Javier Ortega-García. « Variability Compensation Using NAP for Unconstrained Face Recognition ». Dans Advances in Intelligent and Soft Computing, 129–39. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28765-7_17.
Texte intégralMoghekar, Rajeshwar, et Sachin Ahuja. « Face Recognition in Unconstrained Environment Using Deep Learning ». Dans Soft Computing for Intelligent Systems, 241–53. Singapore : Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1048-6_18.
Texte intégralMartin, Michael, et Thirimachos Bourlai. « Unconstrained Face Recognition Using Cell Phone Devices : Faces in the Wild ». Dans Advanced Sciences and Technologies for Security Applications, 129–43. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39489-9_7.
Texte intégralYan, Yan, Hanzi Wang, Cuihua Li, Chenhui Yang et Bineng Zhong. « A Novel Unconstrained Correlation Filter and Its Application in Face Recognition ». Dans Intelligent Science and Intelligent Data Engineering, 32–39. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36669-7_5.
Texte intégralRuiz-del-Solar, Javier, Rodrigo Verschae, Gabriel Hermosilla et Mauricio Correa. « Thermal Face Recognition in Unconstrained Environments Using Histograms of LBP Features ». Dans Local Binary Patterns : New Variants and Applications, 219–43. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39289-4_10.
Texte intégralActes de conférences sur le sujet "Unconstrained face recognition"
Huang, Gary B., Manjunath Narayana et Erik Learned-Miller. « Towards unconstrained face recognition ». Dans 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops). IEEE, 2008. http://dx.doi.org/10.1109/cvprw.2008.4562973.
Texte intégral« Subtasks of Unconstrained Face Recognition ». Dans International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004694201130121.
Texte intégralSrisawasd, Wipawee, et Sartra Wongthanavasu. « Face Recognition In Unconstrained Environment ». Dans 2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE, 2018. http://dx.doi.org/10.1109/jcsse.2018.8457336.
Texte intégralSaffar, Mohammad Taghi, Banafsheh Rekabdar, Sushil Louis et Mircea Nicolescu. « Face recognition in unconstrained environments ». Dans 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, 2015. http://dx.doi.org/10.1109/ijcnn.2015.7280803.
Texte intégralDong-Ju Kim, Sang-Heon Lee, Myoung-Kyu Sohn, Byungmin Kim et Hyunduk Kim. « Face recognition in unconstrained environments ». Dans 2013 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2013. http://dx.doi.org/10.1109/icce.2013.6486832.
Texte intégralShao, Xiaohu, Junliang Xing, Jiangjing Lv, Chunlin Xiao, Pengcheng Liu, Youji Feng et Cheng Cheng. « Unconstrained Face Alignment Without Face Detection ». Dans 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017. http://dx.doi.org/10.1109/cvprw.2017.258.
Texte intégralRoth, Joseph, Yiying Tong et Xiaoming Liu. « Unconstrained 3D face reconstruction ». Dans 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2015. http://dx.doi.org/10.1109/cvpr.2015.7298876.
Texte intégralDao, Viet-Anh, Dang-Ha Nguyen, Viet-Bac Nguyen, Thom Tran Thi et Hoang-Anh Nguyen The. « Face Recognition System for Unconstrained Condition ». Dans 2023 International Conference on Advanced Technologies for Communications (ATC). IEEE, 2023. http://dx.doi.org/10.1109/atc58710.2023.10318921.
Texte intégralTyagi, Ranbeer, Geetam Singh Tomar et Laxmi Shrivastava. « Unconstrained Face Recognition from Image Sequence ». Dans 2023 IEEE World Conference on Applied Intelligence and Computing (AIC). IEEE, 2023. http://dx.doi.org/10.1109/aic57670.2023.10263884.
Texte intégralGunther, M., P. Hu, C. Herrmann, C. H. Chan, M. Jiang, S. Yang, A. R. Dhamija et al. « Unconstrained Face Detection and Open-Set Face Recognition Challenge ». Dans 2017 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2017. http://dx.doi.org/10.1109/btas.2017.8272759.
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