Digital video processing
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov random field modeling in image analysis
Markov random field modeling in image analysis
An HMM-Based Segmentation Method for Traffic Monitoring Movies
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Probabilistic Background Model for Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Segmentations of Spatio-Temporal Images by Spatio-Temporal Markov Random Field Model
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Cast Shadow Detection from a Gaussian Mixture Shadow Model
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Dynamic Conditional Random Field Model for Foreground and Shadow Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Design and Performance of a Fault-Tolerant Real-Time CORBA Event Service
ECRTS '06 Proceedings of the 18th Euromicro Conference on Real-Time Systems
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
Hidden Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Bilateral Markov mesh random field and its application to image restoration
Journal of Visual Communication and Image Representation
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This paper proposes a joint random field (JRF) model for moving vehicle detection in video sequences. The JRF model extends the conditional random field (CRF) by introducing auxilary latent variables to characterize the structure and evolution of visual scene. Hence, detection labels (e.g., vehicle/ roadway) and hidden variables (e.g., pixel intensity under shadow) are jointly estimated to enhance vehicle segmentation in Video sequences. Data-dependent contextual constraints among both detection labels and latent variables are integrated during the detection process. The proposed method handles both moving cast shadows/lights and various weather conditions. Computationally efficient algorithm has been developed for real-time vehicle detection in video streams. Experimental results show that the approach effectively deals with various illumination conditions and robustly detects moving vehicles even in grayscale video.