Sensor models and multisensor integration
International Journal of Robotics Research - Special Issue on Sensor Data Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
3D Tracking = Classification + Interpolation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Tracking Using Foreground-Background Texture Discrimination
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
ACM Computing Surveys (CSUR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Tracking Using Naive Bayesian Classifiers
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Likelihood Map Fusion for Visual Object Tracking
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Multi-sensor Multi-cue Fusion for Object Detection in Video Surveillance
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Real-time tracking with classifiers
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Quality-Based Fusion of Multiple Video Sensors for Video Surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Real-time detection, tracking, recognition, and activity understanding of moving objects from multiple sensors represent fundamental issues to be solved in order to develop surveillance systems that are able to autonomously monitor wide and complex environments. The algorithms that are needed span therefore from image processing to event detection and behaviour understanding, and each of them requires dedicated study and research. In this context, sensor fusion plays a pivotal role in managing the information and improving system performance. Here we present a novel fusion framework for combining the data coming from multiple and possibly heterogeneous sensors observing a surveillance area.