TY - GEN
T1 - Face detection on real low resolution surveillance videos
AU - Cardenas, Rolando Jesus T.
AU - Castañón, César A.Beltrán
AU - Cáceres, Juan Carlos Gutierrez
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/3/23
Y1 - 2018/3/23
N2 - 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%.
AB - 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%.
KW - Face Detection
KW - Haar cascade
KW - LBP
KW - Low-resolution
KW - Optical Flow
KW - Video
UR - http://www.scopus.com/inward/record.url?scp=85048319786&partnerID=8YFLogxK
U2 - 10.1145/3193077.3193084
DO - 10.1145/3193077.3193084
M3 - Conference contribution
AN - SCOPUS:85048319786
T3 - ACM International Conference Proceeding Series
SP - 52
EP - 59
BT - ICCDA 2018 - Proceedings of 2018 the 2nd International Conference on Compute and Data Analysis
PB - Association for Computing Machinery
T2 - 2nd International Conference on Compute and Data Analysis, ICCDA 2018
Y2 - 23 March 2018 through 25 March 2018
ER -