Face Recognition Based on Harris Detector and Convolutional Neural Networks

Zeghina, Assaad Oussama; Zoubia, Oussama; Behloul, Ali

doi:10.1007/978-3-030-58861-8_12

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…William et al67 introduced a face recognition scheme using FaceNet with two pre-trained models, CASIA-WebFace and VGGFace2.• Zeghina et al68 , whose paper implements face recognition based on the Harris detector and CNNs.• Horng et al work…”

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confidence: 99%

Study of image sensors for enhanced face recognition at a distance in the Smart City context

Llauradó,

Pujol,

Tomás

et al. 2023

Sci Rep

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Smart monitoring and surveillance systems have become one of the fundamental areas in the context of security applications in Smart Cities. In particular, video surveillance for Human Activity Recognition (HAR) applied to the recognition of potential offenders and to the detection and prevention of violent acts is a challenging task that is still undergoing. This paper presents a method based on deep learning for face recognition at a distance for security applications. Due to the absence of available datasets on face recognition at a distance, a methodology to generate a reliable dataset that relates the distance of the individuals from the camera, the focal length of the image sensors and the size in pixels of the target face is introduced. To generate the extended dataset, the Georgia Tech Face and Quality Dataset for Distance Faces databases were chosen. Our method is then tested and applied to a set of commercial image sensors for surveillance cameras using this dataset. The system achieves an average accuracy above 99% for several sensors and allows to calculate the maximum distance for a sensor to get the required accuracy in the recognition, which could be crucial in security applications in smart cities.

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confidence: 99%