Paper Info
Title
Combination of colour and thermal sensors for enhanced object detection.
Abstract
In uncontrolled environments, with dynamic background and lighting changes, performing efficient and real-time foreground - background segmentation is very challenging. This work is based on the hypothesis that the combination of long wave infrared (LWIR) (8-12,mu m) and colour cameras can significantly improve the robustness of moving objects extraction. Pros and cons of colour and thermal imagers in outdoor video monitoring applications are discussed. In order to fuse information from both sensors, we favoured an approach based on "analytical fusion" rather than "representative fusion". Starting from a state-of-the-art algorithm for moving objects extraction in colour video (non-parametric codebook model [1]), we first adapted the method for processing of "Red-Green-Blue-Thermal" video format. A preliminary objective performance evaluation of detection accuracy is presented Original image sequences grabbed with co-aligned thermal and visible fields of view was used. Finally, some improvements to the original codebook model are proposed.
Year
DOI
Venue
2007
10.1109/ICIF.2007.4408003
Fusion
Keywords
Field
DocType
image colour analysis,image enhancement,image fusion,image segmentation,image sequences,infrared imaging,object detection,video coding,codebook model,colour-thermal sensors,enhanced object detection,foreground-background segmentation,image fusion,image sequences,long wave infrared camera,moving objects extraction,outdoor video monitoring application,Codebook model,LWIR-colour image fusion,Object detection,Video monitoring
Computer vision,Object detection,Image fusion,Segmentation,Computer science,Robustness (computer science),Image segmentation,Artificial intelligence,Fuse (electrical),Thermal sensors,Codebook
Conference
Citations 
PageRank 
References 
2
0.37
0
Authors
3
Name
Order
Citations
PageRank
Louis St-Laurent1121.89
Xavier Maldague28313.08
Donald Prévost3253.62