Small face detection using deep learning on surveillance videos

Rolando J. Cárdenas; Cesar A. Beltrán; Juan C. Gutiérrez

doi:10.18178/ijmlc.2019.9.2.785

Small face detection using deep learning on surveillance videos

Rolando J. Cárdenas, Cesar A. Beltrán, Juan C. Gutiérrez

Universidad Nacional de San Agustín de Arequipa

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Face detection is one of the essential tasks widely studied in the field of Computer Vision. Several authors have developed different techniques to improve the face detection in images, but these are limited in their application on videos and more if they present low resolution. In this study, we propose a new model for face detection in low-resolution videos based on the morphology of the upper body of people, and the use of Deep Learning (CNN). Our results show an average of 39% accuracy over the Caviar dataset and 32% in the UCSP dataset. Compared with other techniques, our results are greater due they only reach 1% of accuracy.

Original language	English
Pages (from-to)	189-194
Number of pages	6
Journal	International Journal of Machine Learning and Computing
Volume	9
Issue number	2
DOIs	https://doi.org/10.18178/ijmlc.2019.9.2.785
State	Published - 1 Apr 2019

Keywords

Deep learning
Face detection
Low resolution
Video

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10.18178/ijmlc.2019.9.2.785

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title = "Small face detection using deep learning on surveillance videos",

abstract = "Face detection is one of the essential tasks widely studied in the field of Computer Vision. Several authors have developed different techniques to improve the face detection in images, but these are limited in their application on videos and more if they present low resolution. In this study, we propose a new model for face detection in low-resolution videos based on the morphology of the upper body of people, and the use of Deep Learning (CNN). Our results show an average of 39% accuracy over the Caviar dataset and 32% in the UCSP dataset. Compared with other techniques, our results are greater due they only reach 1% of accuracy.",

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AU - Cárdenas, Rolando J.

AU - Beltrán, Cesar A.

AU - Gutiérrez, Juan C.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Face detection is one of the essential tasks widely studied in the field of Computer Vision. Several authors have developed different techniques to improve the face detection in images, but these are limited in their application on videos and more if they present low resolution. In this study, we propose a new model for face detection in low-resolution videos based on the morphology of the upper body of people, and the use of Deep Learning (CNN). Our results show an average of 39% accuracy over the Caviar dataset and 32% in the UCSP dataset. Compared with other techniques, our results are greater due they only reach 1% of accuracy.

AB - Face detection is one of the essential tasks widely studied in the field of Computer Vision. Several authors have developed different techniques to improve the face detection in images, but these are limited in their application on videos and more if they present low resolution. In this study, we propose a new model for face detection in low-resolution videos based on the morphology of the upper body of people, and the use of Deep Learning (CNN). Our results show an average of 39% accuracy over the Caviar dataset and 32% in the UCSP dataset. Compared with other techniques, our results are greater due they only reach 1% of accuracy.

KW - Deep learning

KW - Face detection

KW - Low resolution

KW - Video

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JO - International Journal of Machine Learning and Computing

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Small face detection using deep learning on surveillance videos

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Keywords

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