Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Differential Evolution and Condensation Algorithms for License Plate Tracking
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
ACM Computing Surveys (CSUR)
Rao-Blackwellized particle filter for multiple target tracking
Information Fusion
Joint audio-visual tracking using particle filters
EURASIP Journal on Applied Signal Processing
Robust abandoned object detection using dual foregrounds
EURASIP Journal on Advances in Signal Processing
Tracking moving optima using kalman-based predictions
Evolutionary Computation
Pattern Recognition Letters
Model based human motion tracking using probability evolutionary algorithm
Pattern Recognition Letters
Evaluating multiple object tracking performance: the CLEAR MOT metrics
Journal on Image and Video Processing - Regular
Automatic player detection, labeling and tracking in broadcast soccer video
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interacting MCMC particle filter for tracking maneuvering target
Digital Signal Processing
Real-Time Detection and Tracking for Augmented Reality on Mobile Phones
IEEE Transactions on Visualization and Computer Graphics
Multiple and variable target visual tracking for video-surveillance applications
Pattern Recognition Letters
Control theoretic approach to tracking radar: First step towards cognition
Digital Signal Processing
A grid-based Bayesian approach to robust visual tracking
Digital Signal Processing
Stable multi-target tracking in real-time surveillance video
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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This work presents a novel approach to object detection and tracking in urban environments using images obtained from a radar network, deployed in an urban environment. The proposed system detects, tracks and computes the speed of vehicles and generates alerts when vehicles exceed the predefined road speed limit. The available radar model is a low-cost device oriented to marine environments rather than terrestrial applications. For this reason, we emphasize in the development of a realistic, robust, efficient and effective algorithm which deals with the hardware limitations to provide a suitable overall performance. To reach this objective, we propose dual background subtraction model to detect objects and a tracking method based on the particle filter algorithm. Furthermore, to ensure real time restriction even in HD imagery, our method takes advantage in a natural way of multicore systems and exploits advanced SIMD capabilities available in last multicore processors families. Experimental results demonstrate that the proposed system is able to detect and track multiple objects and to provide speeding alarms when needed. It is also capable to handle target occlusions and disappearances derived from the radar limitations and the noisy urban environment.