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Bayesian Object Tracking

Robust and real-time Bayesian articulated object tracking methods, implemented in C++ and CUDA.

Department(s): Autonomous Motion
Research Projects(s): Probabilistic Object and Manipulator Tracking
Publication(s): Real-time Perception meets Reactive Motion Generation
Probabilistic Articulated Real-Time Tracking for Robot Manipulation
Depth-based Object Tracking Using a Robust Gaussian Filter
The Coordinate Particle Filter - A novel Particle Filter for High Dimensional Systems
Probabilistic Object Tracking Using a Range Camera
Object Tracking in Depth Images Using Sigma Point Kalman Filters
Probabilistic Object Tracking on the GPU
License: GNU General Public License version 3 (GPL-3.0)
Repository: https://github.com/bayesian-object-tracking