Tianfu Wu , Yang Lu and Song-Chun Zhu, Online Object Tracking, Learning and Parsing with And-Or Graphs, arXiv 1509.08067, TPAMI (under revision). http://arxiv.org/abs/1509.08067
See a demo here: https://www.youtube.com/watch?v=1Ian4qzkNLA
The code is written by Matt Tianfu Wu ([email protected]). Please feel free to report issues to him.
Copyright (c) 2016, Matt Tianfu Wu
All rights reserved.
If you find the code is useful in your projects, please consider to cite the paper,
@article{AOGTracker,
author = {Tianfu Wu and
Yang Lu and
Song{-}Chun Zhu},
title = {Online Object Tracking, Learning and Parsing with And-Or Graphs},
journal = {CoRR},
volume = {abs/1509.08067},
year = {2015},
url = {http://arxiv.org/abs/1509.08067},
timestamp = {Thu, 01 Oct 2015 14:28:48 +0200},
biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/WuLZ15b},
bibsource = {dblp computer science bibliography, http://dblp.org}
}
We tested our tracker on Ubuntu 14.04 LTS. Other OS will be supported later on.
sudo apt-get install build-essential cmake libboost1.55-all-dev libopencv-dev libeigen3-dev libfftw3-dev graphviz mpich2
Note: please use libboost1.55-all-dev for the best practice.
It is needed for integrating AOGTracker4VOT into vot-toolkit. Please follow the instrunctions at https://github.com/votchallenge/trax.git.
Assume you put the code at PATH_TO_AOGTracker. It is recommended to build the software in a separate directory. For example
cd PATH_TO_AOGTracker
mkdir build
cd build
Then use CMake to generate the necessary Makefiles with different options (e.g., release version with MPI and VOT support), which you can change accordingly
cmake -DCMAKE_BUILD_TYPE=Release -DRGM_USE_MPI=OFF -DRGM_RUN_VOT=ON ..
Then build the code with
make or make -j 8 (using multithread)
Or, use CMake-gui to do this and use your own favoriate c++ IDE (e.g., Qt creator) to build the code.
After compiling, the release/debug version executables (entry or entryd, AOGTracker4VOT or AOGTracker4VOTd) will be put in PATH_TO_AOGTracker/build/bin
TB100/50 is available at http://cvlab.hanyang.ac.kr/tracker_benchmark/. Please download all the data to PATH_TO_TB100 (e.g. /home/your_user_name/Data/TB100/) Note that: TB100-occ is provided which specifies omitting frame index in TRE (provided by TB-100 authors)
VOT datasets are vailable at http://www.votchallenge.net/. vot-toolkit will download the data automatically.
Change settings in the configuratin xml file, PATH_TO_AOGTracker/config/tracker_config.xml (e.g., specify your data directory, and TB100-occ directory for omitFrameIdxSpecDir, etc)
cd PATH_TO_AOGTracker/build/bin
./entry Tracking PATH_TO_AOGTracker/config/tracker_config.xml
If you have mulitple workstations available, please follow https://help.ubuntu.com/community/MpichCluster to set up the cluster.
cd PATH_TO_AOGTracker/build/bin
/usr/bin/mpiexec.mpich -f machine ./entry Tracking PATH_TO_AOGTracker/config/tracker_config.xml
Note: "machine" is a txt file specifying the cluster machines, and the executable and data directory should be shared among all cluster machines.
We provide the matlab scripts. Run PATH_TO_AOGTracker/matlab/PerfCompTB100/GenPerfPlots_TB100.m
a) Follow the vot-toolkit tutorial to set up the testing environment using matlab.
b) Modify the configuration.m file by adding to the end: set_global_variable('trax_timeout', 20*60);
c) Modify the tracker_AOGTracker.m, e.g.,
tracker_label = ['AOGTracker'];
> for VOT2013, VOT2014 and VOT2015
tracker_command = 'PATH_TO_AOGTracker/build/bin/AOGTracker4VOT PATH_TO_AOGTracker/config/vot_config.xml';
> for VOT-TIR2015
tracker_command = 'PATH_TO_AOGTracker/build/bin/AOGTracker4VOT PATH_TO_AOGTracker/config/vottir_config.xml';
In general, the code is developed with the help from voc-release 5 by Dr. Ross Girshick and Prof. Felzenszwalb. The codes for computing HOG features, FFT convolution and LBFGS are adapted from FFLD by Dr. Charles Dubout http://charles.dubout.ch/en/coding.html. We are grateful to them for making their codes publicly available.