Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
A Hierarchical Approach to Robust Background Subtraction using Color and Gradient Information
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Background Modeling and Subtraction of Dynamic Scenes
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Motion-based background subtraction using adaptive kernel density estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Illumination normalization with time-dependent intrinsic images for video surveillance
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Background estimation under rapid gain change in thermal imagery
Computer Vision and Image Understanding
A hardware architecture for real-time video segmentation utilizing memory reduction techniques
IEEE Transactions on Circuits and Systems for Video Technology
Multi-resolution illumination compensation for foreground extraction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Event detection in underwater domain by exploiting fish trajectory clustering
Proceedings of the 1st ACM international workshop on Multimedia analysis for ecological data
Quantitative performance analysis of object detection algorithms on underwater video footage
Proceedings of the 1st ACM international workshop on Multimedia analysis for ecological data
A rule-based event detection system for real-life underwater domain
Machine Vision and Applications
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Instead of the conventional background and foreground definition, we propose a novel method that decomposes a scene into time-varying background and foreground intrinsic images. The multiplication of these images reconstructs the scene. First, we form a set of previous images into a temporal scale and compute their spatial gradients. By taking advantage of the sparseness of the filter outputs, we estimate the background by median filtering the gradients, and compute the corresponding foreground using the background. We also propose a robust method to threshold foregrounds to obtain a change detection mask of the moving pixels. We show that a different set of filters can detect the static and moving lines. Computationally, the proposed method is comparable with the state of the art, and our simulations prove the effectiveness of the intrinsic background/foreground decomposition even under sudden and severe illumination changes.