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
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Effective Gaussian Mixture Learning for Video Background Subtraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast and Robust Background Updating for Real-time Traffic Surveillance and Monitoring
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A Texture-Based Method for Modeling the Background and Detecting Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Dynamic Light Changes in Outdoor Scenes Without the use of Calibration Objects
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
A Framework for False Positive Suppression in Video Segmentation
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Robust Foreground Detection In Video Using Pixel Layers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foreground Object Detection Using Two Successive Images
AVSS '08 Proceedings of the 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance
Motion Detection Based on Background Modeling and Performance Analysis for Outdoor Surveillance
ICCMS '09 Proceedings of the 2009 International Conference on Computer Modeling and Simulation
Background Subtraction for Temporally Irregular Dynamic Textures
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Independent component analysis-based background subtraction for indoor surveillance
IEEE Transactions on Image Processing
Spatiotemporal Saliency in Dynamic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive shadow estimator for removing shadow of moving object
Computer Vision and Image Understanding
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
Integrating intensity and texture differences for robust change detection
IEEE Transactions on Image Processing
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
Region-Level Motion-Based Background Modeling and Subtraction Using MRFs
IEEE Transactions on Image Processing
A novel background subtraction method based on color invariants
Computer Vision and Image Understanding
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To solve the problem due to fast illumination change in a visual surveillance system, we propose a novel moving object detection algorithm for which we develop an illumination change model, a chromaticity difference model, and a brightness ratio model. When fast illumination change occurs, background pixels as well as moving object pixels are detected as foreground pixels. To separate detected foreground pixels into moving object pixels and false foreground pixels, we develop a chromaticity difference model and a brightness ratio model that estimates the intensity difference and intensity ratio of false foreground pixels, respectively. These models are based on the proposed illumination change model. Based on experimental results, the proposed method shows excellent performance under various illumination change conditions while operating in real-time.