TY - GEN
T1 - Pedestrian tracking in the compressed domain using thermal images
AU - Lahouli, Ichraf
AU - Haelterman, Robby
AU - Chtourou, Zied
AU - De Cubber, Geert
AU - Attia, Rabah
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - The video surveillance of sensitive facilities or borders poses many challenges like the high bandwidth requirements and the high computational cost. In this paper, we propose a framework for detecting and tracking pedestrians in the compressed domain using thermal images. Firstly, the detection process uses a conjunction between saliency maps and contrast enhancement techniques followed by a global image content descriptor based on Discrete Chebychev Moments (DCM) and a linear Support Vector Machine (SVM) as a classifier. Secondly, the tracking process exploits raw H.264 compressed video streams with limited computational overhead. In addition to two, well-known, public datasets, we have generated our own dataset by carrying six different scenarios of suspicious events using a thermal camera. The obtained results show the effectiveness and the low computational requirements of the proposed framework which make it suitable for real-time applications and onboard implementation.
AB - The video surveillance of sensitive facilities or borders poses many challenges like the high bandwidth requirements and the high computational cost. In this paper, we propose a framework for detecting and tracking pedestrians in the compressed domain using thermal images. Firstly, the detection process uses a conjunction between saliency maps and contrast enhancement techniques followed by a global image content descriptor based on Discrete Chebychev Moments (DCM) and a linear Support Vector Machine (SVM) as a classifier. Secondly, the tracking process exploits raw H.264 compressed video streams with limited computational overhead. In addition to two, well-known, public datasets, we have generated our own dataset by carrying six different scenarios of suspicious events using a thermal camera. The obtained results show the effectiveness and the low computational requirements of the proposed framework which make it suitable for real-time applications and onboard implementation.
UR - https://www.scopus.com/pages/publications/85065876550
U2 - 10.1007/978-3-030-19816-9_3
DO - 10.1007/978-3-030-19816-9_3
M3 - Conference contribution
AN - SCOPUS:85065876550
SN - 9783030198152
T3 - Communications in Computer and Information Science
SP - 35
EP - 44
BT - Representations, Analysis and Recognition of Shape and Motion from Imaging Data - 7th International Workshop, RFMI 2017, Revised Selected Papers
A2 - Chen, Liming
A2 - Ghorbel, Faouzi
A2 - Ben Amor, Boulbaba
PB - Springer
T2 - 7th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2017
Y2 - 17 December 2017 through 20 December 2017
ER -