Visual Surveillance for Moving Vehicles
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Reactive Tabu Search and Sensor Selection in Active Structural Acoustic Control Problems
Journal of Heuristics
2D-Object Tracking Based on Projection-Histograms
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Guided Local Search for Final Placement in VLSI Design
Journal of Heuristics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Using a genetic algorithm for multi-hypothesis tracking
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Image registration with iterated local search
Journal of Heuristics
Constraint-Based Local Search
The equation for response to selection and its use for prediction
Evolutionary Computation
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
IEEE Transactions on Evolutionary Computation
Improving the accuracy of action classification using view-dependent context information
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
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Intelligent Visual Surveillance (IVS) systems are becoming a ubiquitous security component as they aim at monitoring, in real time, persistent and transcient activities in specific environments. This paper considers the data association problem arising in IVS systems, which consists in assigning blobs (connected sets of pixels) to tracks (objects being monitored) in order to minimize the distance of the resulting scene to its prediction (which may be obtained with a Kalman filter). It proposes a tabu-search algorithm for this multi-assignment problem that can process more than 11 frames per seconds on standard IVS benchmarks, thus significantly outperforming the state of the art.