research-article

Face Detection on real Low Resolution Surveillance Videos

Authors:

Rolando Jesus Cardenas T.,

César A. Beltrán Castañón,

Juan Carlos Gutiérrez CáceresAuthors Info & Claims

ICCDA '18: Proceedings of the 2nd International Conference on Compute and Data Analysis

Pages 52 - 59

https://doi.org/10.1145/3193077.3193084

Published: 23 March 2018 Publication History

Abstract

The use of video cameras for security reasons has increased in recent times. Identify a person with automatic face detection systems have greater importance today; but the low-quality of the videos make it difficult and are still an open problem that many researchers are trying to solve. We propose a novel methodology for face detection on low-resolution videos based on parallel Gunnar Farnebäck optical flow algorithm, Haar Cascades and Local Binary Patterns. Our model does not use illumination normalization or super-resolution techniques, commonly used in literature. The results on the Caviar Database prove a better detection rate compared with OpenCv Library, Dlib C++ Library and Matlab function, which use the known Viola-Jones Haar cascade algorithm and HOGs. Even though these tools not have a number of detections up to 1%, our proposal can detect faces in a rate of 50%.

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Cited By

Selvi EAdimoolam MKarthi GThinakaran KBalamurugan NKannadasan RWechtaisong CKhan A(2022)Suspicious Actions Detection System Using Enhanced CNN and Surveillance VideoElectronics10.3390/electronics1124421011:24(4210)Online publication date: 16-Dec-2022
https://doi.org/10.3390/electronics11244210
Casanova GYandun DGuerrero G(2020)Analysis of video surveillance images using computer vision in a controlled security environment2020 15th Iberian Conference on Information Systems and Technologies (CISTI)10.23919/CISTI49556.2020.9141068(1-6)Online publication date: Jun-2020
https://doi.org/10.23919/CISTI49556.2020.9141068

Index Terms

Face Detection on real Low Resolution Surveillance Videos
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Other conferences

ICCDA '18: Proceedings of the 2nd International Conference on Compute and Data Analysis

March 2018

94 pages

ISBN:9781450363594

DOI:10.1145/3193077

Copyright © 2018 ACM.

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Publication History

Published: 23 March 2018

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ICCDA 2018: 2018 The 2nd International Conference on Compute and Data Analysis

March 23 - 25, 2018

IL, DeKalb, USA

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Cited By

Selvi EAdimoolam MKarthi GThinakaran KBalamurugan NKannadasan RWechtaisong CKhan A(2022)Suspicious Actions Detection System Using Enhanced CNN and Surveillance VideoElectronics10.3390/electronics1124421011:24(4210)Online publication date: 16-Dec-2022
https://doi.org/10.3390/electronics11244210
Casanova GYandun DGuerrero G(2020)Analysis of video surveillance images using computer vision in a controlled security environment2020 15th Iberian Conference on Information Systems and Technologies (CISTI)10.23919/CISTI49556.2020.9141068(1-6)Online publication date: Jun-2020
https://doi.org/10.23919/CISTI49556.2020.9141068

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