Chromatic sensitivity of illumination change compensation techniques

Authors:
M. Ryan Bales;Dana Forsthoefel;D. Scott Wills;Linda M. Wills
Affiliations:
Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA;Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA;Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA;Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Year:
2010

Citing 8
Cited 1

Robot Vision

Robot Vision
Real-time tracking of image regions with changes in geometry and illumination

CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Model Estimation for Photometric Changes of Outdoor Planar Color Surfaces Caused by Changes in Illumination and Viewpoint

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Color Illumination Models for Image Matching and Indexing

ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Locale-Based Visual Object Retrieval under Illumination Change

ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Illumination-Invariant Color Object Recognition via Compressed Chromaticity Histograms of Color-Channel-Normalized Images

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Online Learning of Color Transformation for Interactive Object Recognition under Various Lighting Conditions

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Global brightness-variation compensation for video coding

IEEE Transactions on Circuits and Systems for Video Technology

Bigbackground-based illumination compensation for surveillance video

Journal on Image and Video Processing - Special issue on advanced video-based surveillance

Quantified Score

Hi-index	0.00

Visualization

Abstract

Illumination changes and their effects on scene appearance pose serious problems to many computer vision algorithms. In this paper, we present the benefits that a chromaticity-based approach can provide to illumination compensation. We consider three computationally inexpensive illumination models, and demonstrate that customizing these models for chromatically dissimilar regions reduces mean absolute difference (MAD) error by 70% to 80% over computing the models globally for the entire image. We demonstrate that models computed for a given color are somewhat effective for different colors with similar hues (increasing MAD error by a factor of 6), but are ineffective for colors with dissimilar hues (increasing MAD error by a factor of 15). Finally, we find that model choice is less important if the model is customized for chromatically dissimilar regions. Effects of webcamera drivers are considered.