Face Recognition Using Neural Network: A Review

Kasar, Manisha M.; Bhattacharyya, Debnath; Kim, Tai-hoon

doi:10.14257/ijsia.2016.10.3.08

Cited by 94 publications

(49 citation statements)

References 16 publications

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“…Este justamente es el método utilizado por los autores del HOG debido a su desempeño. También es común encontrar el uso de redes neuronales para el proceso de entrenamiento [13]. Sin importar el método escogido, la idea es realizar un entrenamiento previo con imágenes de rostros (muestras positivas) y no rostros (muestras negativas).…”

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Reconocimiento de rostros en tiempo real sobre dispositivos móviles de bajo costo

López

Torres

2018

Lámpsakos

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Resumen: Se prueban algunos de los métodos más conocidos de reconocimiento de rostros, para determinar su utilidad real en la construcción de aplicaciones en tiempo real que puedan ejecutarse sobre un dispositivo móvil de bajo costo. Con este fin, se realiza una breve descripción de los principales algoritmos utilizados en aplicaciones de reconocimiento de rostros y se muestra cómo la fase de detección de rostros es de vital importancia en cuanto a desempeño se refiere en estos dispositivos. Se demuestra además la imposibilidad de realizar el procesamiento de cada frame de un stream de video, a una rata de 30 frames por segundo, con los métodos revisados.Palabras clave: Análisis de desempeño, Computación móvil, Reconocimiento de rostros.Abstract: Some of the most recognized face recognition methods are tested to determine their usefulness in the construction of real-time mobile applications, intended to a low-cost mobile market. To this end, a brief description of the main algorithms used in face recognition applications is made. It is shown how face detection phase is vital in terms of performance on these devices. It is also demonstrated the impossibility of performing the processing of each frame of a video stream, which runs at a rate of 30 frames per second, using the considered methods.

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“…El survey [22] resume un conjunto de trabajos en los que se hace uso de Deep Learning para el reconocimiento de rostros. De forma similar el trabajo [13] muestra cómo se pueden usar diversos tipos de redes neuronales, en las diferentes fases del reconocimiento de rostros.…”

Section: Reconocimiento De Rostrosunclassified

Reconocimiento de rostros en tiempo real sobre dispositivos móviles de bajo costo

López

Torres

2018

Lámpsakos

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“…In [9], it is done a research on different face recognition techniques for biometric systems. They showed the advantages of different NN approaches compared to other methods, as well as the current limitations.…”

Section: Related Workmentioning

confidence: 99%

A Face Recognition Library using Convolutional Neural Networks

Blanger¹,

Panisson²

2017

Engineering Journal

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“…The input of face recognition system is normally a digital image or video stream and the output is an identification or verification of the person that appear in the image or video stream [41]. Several approaches define a face recognition system as a three step process as shown in Figure 1.…”

Section: A Generic Face Recognition Systemmentioning

confidence: 99%

Face Recognition: A Literature Review

Barnouti¹,

Al-Dabbagh²,

Matti³

2016

IJAIS

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Face recognition have gained a great deal of popularity because of the wide range of applications such as in entertainment, smart cards, information security, law enforcement, and surveillance. It is a relevant subject in pattern recognition, computer vision, and image processing. Two major methods are used for features extraction, which can be classified into appearance-based and Model-based methods.Appearance-based methods use global representations to identify a face. Model-based face methods aim to construct a model of the human face that capture facial variations. Image similarity is the distance between the vectors of two images. This paper contains Four sections. The first section discusses face recognition applications with examples. The second section discuss the common feature face recognition methods. The third section discuss distance measurement classifiers. The fourth section discuss different face recognition databases.

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Face Recognition Using Neural Network: A Review

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Cited by 94 publications

References 16 publications

Reconocimiento de rostros en tiempo real sobre dispositivos móviles de bajo costo

Reconocimiento de rostros en tiempo real sobre dispositivos móviles de bajo costo

A Face Recognition Library using Convolutional Neural Networks

Face Recognition: A Literature Review

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