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.
Index Terms—Deep learning, face detection, low resolution, video.
Rolando J. Cárdenas and Juan C. Gutiérrez are with National University of San Agustin – UNSA, Arequipa, Peru (e-mail: firstname.lastname@example.org, email@example.com).
Cesar A. Beltrán is Pontificia Universidad Católica del Perú – PUCP, Artificial Intelligence Research Group (IA-PUCP), Lima, Peru (e-mail: firstname.lastname@example.org).
Cite: Rolando J. Cárdenas, Cesar A. Beltrán, and Juan C. Gutiérrez, "Small Face Detection Using Deep Learning on Surveillance Videos," International Journal of Machine Learning and Computing vol. 9, no. 2, pp. 189-194, 2019.