Advanced surveillance systems: combining video and thermal imagery for pedestrian detection

2004 ◽  
Author(s):  
Helene Torresan ◽  
Benoit Turgeon ◽  
Clemente Ibarra-Castanedo ◽  
Patrick Hebert ◽  
Xavier P. Maldague
Keyword(s):  
Pedestrian Detection ◽  
Surveillance Systems ◽  
Thermal Imagery

ADDRESSING THE PROBLEMS OF DETECTING FACES WITH NEURAL NETWORKS

2007 ◽  
Vol 07 (04) ◽  
pp. 617-640 ◽  
Author(s):  
KEVIN CURRAN ◽  
NEIL McCAUGHLEY ◽  
XUELONG LI
Keyword(s):  
Face Detection ◽  
Detection System ◽  
Pedestrian Detection ◽  
Image Sequences ◽  
Database Management System ◽  
Surveillance Systems ◽  
Human Computer Interface ◽  
Human Machine Interaction ◽  
The Face ◽  
Machine Interaction

The face is the most distinctive and widely used key to a person's identity. The area of face detection has attracted considerable attention in the advancement of human-machine interaction as it provides a natural and efficient way to communicate between humans and machines. The problem of facial parts in image sequences has become a popular area of research due to emerging applications in intelligent human-computer interface, surveillance systems, content-based image retrieval, video conferencing, financial transaction, forensic applications, pedestrian detection, image database management system and so on. This paper presents the results of an image based neural network face detection system which seeks to address the problem of detecting faces under gross variations.

scholarly journals Pedestrian age estimation based on deep learning

2021 ◽  
Vol 22 (3) ◽  
pp. 1548
Author(s):  
Nawal Younis Abdullah ◽  
Mohammed Talal Ghazal ◽  
Najwan Waisi
Keyword(s):  
Age Estimation ◽  
Large Scale ◽  
Pedestrian Detection ◽  
Age Groups ◽  
Model Performance ◽  
Surveillance Systems ◽  
Estimation Model ◽  
Deep Convolutional Neural Networks ◽  
Detection Algorithms ◽  
Deep Convolution Neural Network

The large-scale distribution of camera networks in the traffic area resulted in the increasing popularity of video surveillance systems. As pedestrian detection and tracking are the critical monitoring targets in traffic surveillance, many studies focus on pedestrian detection algorithms across cameras. This paper addressed the effect of using the age estimation based on deep convolution neural network (CNN) as a convenience for pedestrian monitoring who is crossing at intersections. Two popular deep convolutional neural networks (DCNNs) pre-trained models have been used in this work, which have recently achieved the best performance in facial features extraction tasks: VGG-Face and ResNet-50. We combined these two models to increase the efficiency of the proposed system. We ran our experiments to evaluate the system based on the VGGFace2 dataset consisting of 3.31 million face images. From the experimental results, we observed a gap in the detection performances between those age groups: children from (00-10) years and elderly with 55 years and more. Moreover, it noted that the proposed pedestrian age estimation model performance is high, also a good result can be obtained by using the model for new purpose.

A Low-Complexity Pedestrian Detection Framework for Smart Video Surveillance Systems

2017 ◽  
Vol 27 (10) ◽  
pp. 2260-2273 ◽  
Author(s):  
Muhammad Bilal ◽  
Asim Khan ◽  
Muhammad Umar Karim Khan ◽  
Chong-Min Kyung
Keyword(s):  
Video Surveillance ◽  
Pedestrian Detection ◽  
Low Complexity ◽  
Surveillance Systems

scholarly journals Robust pedestrian detection in thermal imagery using synthesized images

2021 ◽  
Author(s):  
My Kieu ◽  
Lorenzo Berlincioni ◽  
Leonardo Galteri ◽  
Marco Bertini ◽  
Andrew D. Bagdanov ◽  
...  
Keyword(s):  
Pedestrian Detection ◽  
Thermal Imagery
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