The core of this library are two probabilistic tracker
- A Non-Parametric Tracker Based on Rao-Blackwellized Coordinate Descent Particle Filter
[M. Wuthrich, P. Pastor, M. Kalakrishnan, J. Bohg, and S. Schaal. Probabilistic Object Tracking using a Range Camera IEEE Intl Conf on Intelligent Robots and Systems, 2013]
http://arxiv.org/abs/1505.00241
This tracker can run on a pure CPU system or optionally run on GPU using CUDA 6.5 or later
-
A Parametric Tracker Based on Robust Multi-Sensor Gaussian Filter Tracker
[J. Issac, M. Wuthrich, C. Garcia Cifuentes, J. Bohg, S. Trimpe, S. Schaal Depth-Based Object Tracking Using a Robust Gaussian Filter IEEE Intl Conf on Robotics and Automation, 2016]
All trackers require mesh models in Wavefront (.obj) format.
- Ubuntu 12.04
- C++0x or C++11 Compiler (gcc-4.6 or later)
- CUDA 6.5 or later (optional)
- Filtering library (fl)
- Eigen 3.2.1 or later
The cmake package uses Catkin. If you have installed ROS groovy or later, then you most likely have catkin installed already.
$ cd $HOME
$ mkdir -p projects/tracking/src
$ cd projects/tracking/src
$ git clone git@github.com:filtering-library/fl.git
$ git clone git@github.com:bayesian-object-tracking/dbot.git
$ cd ..
$ catkin_make -DCMAKE_BUILD_TYPE=Release -DDBOT_BUILD_GPU=On
If no CUDA enabled device is available, you can deactivate the GPU implementation via
$ catkin_make -DCMAKE_BUILD_TYPE=Release -DDBOT_BUILD_GPU=Off
Checkout the ros nodes of each tracker in dbot_ros package for exact usage of the filters.