Reconocimiento facial en tiempo real orientado a video llamadas o live stream para autenticar identidades durante una audiencia legal
dc.contributor.advisor | Pardo Beainy, Camilo | spa |
dc.contributor.advisor | Rodríguez Caro, Daniel | spa |
dc.contributor.author | Pardo Morcote, Julián David | spa |
dc.coverage.campus | CRAI-USTA Tunja | spa |
dc.date.accessioned | 2020-10-20T17:11:47Z | spa |
dc.date.available | 2020-10-20T17:11:47Z | spa |
dc.date.issued | 2020-10-17 | spa |
dc.description | En este libro se encuentra la descripción del diseño y desarrollo de la aplicación para reconocimiento facial en tiempo real, se documenta todo el desarrollo de esta herramienta con alta calidad investigativa y buenos resultados en las pruebas realizadas, con el fin de aportar una solución a la problemática de suplantación de identidades, estableciendo como objetivo crear una herramienta informática para autenticar identidades durante video llamadas, que se construyó gracias a la herramienta DLIB una librería que ayuda a detectar objetos, en este caso el rostro de una persona. Se implementó el método ingenieril con enfoque aplicativo ya que no cualifica ni cuantifica variables y en conclusión se obtiene un software especializado en reconocimiento biométrico facial de alta fiabilidad, convirtiendo a este libro en una fuente de consulta seria y organizada que aporta conocimiento a la academia y a los ingenieros electrónicos que deseen realizar una investigación relacionada con reconocimiento biométrico facial. | spa |
dc.description.abstract | In this book you will find the description of the design and development of the application for facial recognition in real time, the entire development of this tool is documented with high investigative quality and good results in the tests carried out, in order to provide a solution to the problem of identity theft, establishing the objective of creating a IT tool to authenticate identities during video calls, which was built thanks to the DLIB tool, a library that helps to detect objects, in this case the face of a person. The engineering method with an applicative approach was implemented since it does not qualify or quantifies variables and in conclusion a specialized recognition software is obtained highly reliable facial biometric, making this book a source for serious and organized that brings knowledge to academia and electronic engineers who want conduct research related to biometric facial recognition. | spa |
dc.description.degreelevel | Pregrado | spa |
dc.description.degreename | Ingeniero Electronico | spa |
dc.format.mimetype | application/pdf | spa |
dc.identifier.citation | Pardo, J. (2020). Reconocimiento facial en tiempo real orientado a video llamadas o live stream para autenticar identidades durante una audiencia legal Tesis Ingeniería Electrónica. Universidad Santo Tomas Tunja | spa |
dc.identifier.instname | instname:Universidad Santo Tomás | spa |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad Santo Tomás | spa |
dc.identifier.repourl | repourl:https://repository.usta.edu.co | spa |
dc.identifier.uri | http://hdl.handle.net/11634/30508 | |
dc.language.iso | spa | spa |
dc.publisher | Universidad Santo Tomás | spa |
dc.publisher.faculty | Facultad de Ingeniería Electrónica | spa |
dc.publisher.program | Pregrado Ingeniería Electrónica | spa |
dc.relation.references | Presente y futuro del reconocimiento facial. (n.d.). Retrieved June 16, 2020, from https://www.padigital.es/tendencias-digitales/historia-y-evolucion-del-reconocimiento-facial.html | spa |
dc.relation.references | Dlib C++ Library: High Quality Face Recognition with Deep Metric Learning. (n.d.). Retrieved June 16, 2020, from http://blog.dlib.net/2017/02/high-quality-face-recognition-with-deep.html | spa |
dc.relation.references | Machine Learning is Fun! Part 4: Modern Face Recognition with Deep Learning. (n.d.). Retrieved June 16, 2020, from https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-facerecognition-with-deep-learning-c3cffc121d78 | spa |
dc.relation.references | Ketkar, N. (2017). Deep Learning with Python. In Deep Learning with Python. https://doi.org/10.1007/978- 1-4842-2766-4 | spa |
dc.relation.references | Lutz, M. (2007). Learning Python. In Icarus. https://doi.org/10.1016/0019-1035(89)90077-8 | spa |
dc.relation.references | Bradski, G., & Kaehler, A. (2008). Learning OpenCV. In Learning OpenCV. https://doi.org/10.1109/MRA.2009.933612 | spa |
dc.relation.references | Zelinsky, A. (2009). Learning OpenCV—Computer Vision with the OpenCV Library. In IEEE Robotics and Automation Magazine. https://doi.org/10.1109/MRA.2009.933612 | spa |
dc.relation.references | Programming python. (1997). Computers & Mathematics with Applications. https://doi.org/10.1016/s0898- 1221(97)82952-5 | spa |
dc.relation.references | Howse, J. (2013). OpenCV Computer Vision with Python. In Cs_Python_in. https://doi.org/10.1017/CBO9781107415324.004 | spa |
dc.relation.references | Itseez. (2012). OpenCV - Open Source Computer Vision. Online Webpage. | spa |
dc.relation.references | Xie, Z., Li, J., & Shi, H. (2019). A Face Recognition Method Based on CNN. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1395/1/012006 | spa |
dc.relation.references | Yaswanth, V. V. S., & Devi, T. (2019). Automatic emotion recognition using facial expression by python. Test Engineering and Management. | spa |
dc.relation.references | ADIEGO RODRIGUEZ, J. (2007). books google. Obtenido de https://books.google.es/books?id=FfEfCBhXCgC&pg=PT297&dq=base+datos+relacional+codd&hl=es&sa=X&ved=0ahUKEwjixf LYxcPXAhXMWhQKHQImAfUQ6AEIQjAF#v=onepage&q=base%20datos%20relacio nal%20codd&f=false | spa |
dc.relation.references | Amos, B. (septiembre de 2016). ResearchGate. Obtenido de ResearchGate: https://www.researchgate.net/figure/The-68-landmarks-detected-by-dlib-library-Thisimage-was-created-by-Brandon-Amos-of-CMU_fig2_329392737 | spa |
dc.relation.references | Arce, J. I. (26 de julio de 2019). health Big Data. Obtenido de https://www.juanbarrios.com/matrizde-confusion-y-sus-metricas/ | spa |
dc.relation.references | Boyko, N., Basystiuk, O., & Shakhovska, N. (2018). Performance Evaluation and Comparison of Software for Face Recognition, Based on Dlib and Opencv Library. IEEE explore. | spa |
dc.relation.references | contabal. (2016). Obtenido de https://www.contaval.es/que-es-la-vision-artificial-y-para-quesirve/ | spa |
dc.relation.references | Duque, R. G. (2020). Python para todos. En R. G. Duque, Python para todos. | spa |
dc.relation.references | Geitgey, A. (2017). Readthedocs. Obtenido de Readthedocs: https://facerecognition.readthedocs.io/en/latest/face_recognition.html | spa |
dc.relation.references | Guay, M. (2010). how to geek. Obtenido de https://www.howtogeek.com/howto/17528/changethe-user-interface-language-in-ubuntu/ | spa |
dc.relation.references | Inovation, A. (2019). Atria Inovation. Obtenido de https://www.atriainnovation.com/que-son-lasredes-neuronales-y-sus-funciones/ | spa |
dc.relation.references | King, D. (2017). http://blog.dlib.net/. Obtenido de http://blog.dlib.net/: http://blog.dlib.net/ | spa |
dc.relation.references | Na8. (28 de noviembre de 2019). como funcionan las convolutional neural networks? Obtenido de aprende machine learnign: https://www.aprendemachinelearning.com/como-funcionanlas-convolutional-neural-networks-vision-por-ordenador/ | spa |
dc.relation.references | NetCloud. (2019). Obtenido de https://netcloudengineering.com/funcionamiento-redes-lan/ | spa |
dc.relation.references | Opencv.org. (2020). Opencv. Obtenido de Opencv: https://opencv.org/about/ | spa |
dc.relation.references | PADigital. (27 de noviembre de 2018). padigital.es. Obtenido de https://www.padigital.es/tendencias-digitales/historia-y-evolucion-del-reconocimientofacial.html#:~:text=Los%20inicios%20del%20reconocimiento%20facial,trav%C3%A9s %20de%20la%20tabla%20RAND. | spa |
dc.relation.references | Quintana, J. (mayo de 2018). medium.com. Obtenido de medium.com: https://medium.com/datosy-ciencia/modelos-cnn-en-la-clasificaci%C3%B3n-de-im%C3%A1genescl%C3%A1sicas-y-modernas-d072a6718689 | spa |
dc.relation.references | Rajesh, K. M., & Naveenkumar, M. (2016). A robust method for face recognition and face emotion detection system using support vector machines. IEEE explore. | spa |
dc.relation.references | Rivera, M. (Agosto de 2019). resnet.md. Obtenido de resnet.md: http://personal.cimat.mx:8181/~mrivera/cursos/aprendizaje_profundo/resnet/resnet.html | spa |
dc.relation.references | Russell, S. J., & Norvig, P. N. (2009). Artificial intelligence: a modern approach. En S. J. Russell, & P. N. Norvig. | spa |
dc.relation.references | Sampieri, R. (2014). Metodología de la investigación 6ta Edición. McGRAW-HILL / INTERAMERICANA EDITORES, S.A. DE C.V. | spa |
dc.relation.references | significados.com. (2020). Obtenido de https://www.significados.com/software/ | spa |
dc.relation.references | Sphinx. (2019). https://pyautogui.readthedocs.io/en/latest/. Obtenido de https://pyautogui.readthedocs.io/en/latest/: https://pyautogui.readthedocs.io/en/latest/ | spa |
dc.relation.references | tecnologia informatica. (2020). Obtenido de https://www.tecnologia-informatica.com/algoritmodefinicion/ | spa |
dc.relation.references | Thilaga, P. J., Khan, B. A., Jones, A., & Kumar, N. K. (2018). Modern Face Recognition with Deep Learning. IEEE explore. | spa |
dc.relation.references | zator.com. (2020). Obtenido de zator. | spa |
dc.rights | Atribución-NoComercial-SinDerivadas 2.5 Colombia | * |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
dc.rights.local | Abierto (Texto Completo) | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | * |
dc.subject.keyword | facial recognition | spa |
dc.subject.keyword | Dlib | spa |
dc.subject.keyword | neural networks | spa |
dc.subject.keyword | artificial vision | spa |
dc.subject.keyword | artificial intelligence | spa |
dc.subject.keyword | Python | spa |
dc.subject.proposal | reconocimiento facial | spa |
dc.subject.proposal | Dlib | spa |
dc.subject.proposal | redes neuronales | spa |
dc.subject.proposal | visión artificial | spa |
dc.subject.proposal | inteligencia artificial | spa |
dc.subject.proposal | Python | spa |
dc.title | Reconocimiento facial en tiempo real orientado a video llamadas o live stream para autenticar identidades durante una audiencia legal | spa |
dc.type | bachelor thesis | |
dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
dc.type.drive | info:eu-repo/semantics/bachelorThesis | |
dc.type.local | Tesis de pregrado | spa |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
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