On the representation and estimation of spatial uncertainly
International Journal of Robotics Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking People in a Railway Station During Rush-Hour
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
Merging Gaussian Distributions for Object Localization in Multi-robot Systems
ISER '00 Experimental Robotics VII
Multi-modal tracking of people using laser scanners and video camera
Image and Vision Computing
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating multiple object tracking performance: the CLEAR MOT metrics
Journal on Image and Video Processing - Regular
A novel system for tracking pedestrians using multiple single-row laser-range scanners
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A Multiple-Hypothesis Approach for Multiobject Visual Tracking
IEEE Transactions on Image Processing
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In this paper the problem of tracking walking people with multiple moving robots is tackled. For this purpose we present an adaptation to the Multiple Hypothesis Tracking method, which unlike classic MHT, allows for one-to-many associations between targets and measurements in each hypothesis production cycle and is thus capable of operating in a scenario involving multiple sensors. Derivation of hypotheses probabilities accounts for the continuously changing overlapping areas in fields of view of the robots sensors and for detection uncertainty. In the context of three experiments involving people walking among moving robots, the successful integration of our tracking algorithm to a real-world setup is assessed.