Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
An HMM-Based Segmentation Method for Traffic Monitoring Movies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Fast Gauss Transform and Efficient Kernel Density Estimation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Comparing Belief Propagation and Graph Cuts for Novelty Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
ACM Computing Surveys (CSUR)
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
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
Algorithmic and Architectural Optimizations for Computationally Efficient Particle Filtering
IEEE Transactions on Image Processing
Patchwise scaling method for content-aware image resizing
Signal Processing
Investigation on tracking system for real time video surveillance applications
Proceedings of the CUBE International Information Technology Conference
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The color similarity between the background and foreground causes serious misdetections in moving object detection from video sequences. In this paper, we point out that the existence of a confusion point and the model inaccuracy are the reasons for the misdetections due to the color similarity. Accordingly, the solutions of the color similarity are to shift the confusion point and to improve the model accuracy. Based on this conclusion, a simple algorithm by combining a weighting technique and a new foreground model is presented, and improved results are generated. More accurate weighting techniques and foreground models are expected to be developed in the future based on the solutions.