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external.txt
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NOTE: Our code is based on KCF and here are information of the KCF:
High-Speed Tracking with Kernelized Correlation Filters
J. F. Henriques R. Caseiro P. Martins J. Batista
TPAMI 2014
________________
To be published.
arXiv pre-print: http://arxiv.org/abs/1404.7584
Project webpage: http://www.isr.uc.pt/~henriques/circulant/
This MATLAB code implements a simple tracking pipeline based on the Kernelized
Correlation Filter (KCF), and Dual Correlation Filter (DCF).
It is free for research use. If you find it useful, please acknowledge the paper
above with a reference.
__________
Quickstart
1. Extract code somewhere.
2. The tracker is prepared to run on any of the 50 videos of the Visual Tracking
Benchmark [3]. For that, it must know where they are/will be located. You can
change the default location 'base_path' in 'download_videos.m' and 'run_tracker.m'.
3. If you don't have the videos already, run 'download_videos.m' (may take some time).
4. Execute 'run_tracker' without parameters to choose a video and test the KCF on it.
__________
The main interface function is 'run_tracker'. You can test several configurations (KCF,
DCF, MOSSE) by calling it with different commands:
run_tracker
Without any parameters, will ask you to choose a video, track using
the Gaussian KCF on HOG, and show the results in an interactive
figure. Press 'Esc' to stop the tracker early. You can navigate the
video using the scrollbar at the bottom.
run_tracker VIDEO
Allows you to select a VIDEO by its name. 'all' will run all videos
and show average statistics. 'choose' will select one interactively.
run_tracker VIDEO KERNEL
Choose a KERNEL. 'gaussian'/'polynomial' to run KCF, 'linear' for DCF.
run_tracker VIDEO KERNEL FEATURE
Choose a FEATURE type, either 'hog' or 'gray' (raw pixels).
run_tracker(VIDEO, KERNEL, FEATURE, SHOW_VISUALIZATION, SHOW_PLOTS)
Decide whether to show the scrollable figure, and the precision plot.
Useful combinations:
>> run_tracker choose gaussian hog %Kernelized Correlation Filter (KCF)
>> run_tracker choose linear hog %Dual Correlation Filter (DCF)
>> run_tracker choose gaussian gray %Single-channel KCF (ECCV'12 paper)
>> run_tracker choose linear gray %MOSSE filter (single channel)
For the actual tracking code, check out the 'tracker' function.
Though it's not required, the code will make use of the MATLAB Parallel Computing
Toolbox automatically if available.
__________
References
[1] J. F. Henriques, R. Caseiro, P. Martins, J. Batista, "High-Speed Tracking with
Kernelized Correlation Filters", TPAMI 2014 (to be published).
[2] J. F. Henriques, R. Caseiro, P. Martins, J. Batista, "Exploiting the Circulant
Structure of Tracking-by-detection with Kernels", ECCV 2012.
[3] Y. Wu, J. Lim, M.-H. Yang, "Online Object Tracking: A Benchmark", CVPR 2013.
Website: http://visual-tracking.net/
[4] P. Dollar, "Piotr's Image and Video Matlab Toolbox (PMT)".
Website: http://vision.ucsd.edu/~pdollar/toolbox/doc/index.html
[5] P. Dollar, S. Belongie, P. Perona, "The Fastest Pedestrian Detector in the
West", BMVC 2010.
_____________________________________
Copyright (c) 2014, Joao F. Henriques
Permission to use, copy, modify, and distribute this software for research
purposes with or without fee is hereby granted, provided that the above
copyright notice and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
_______________________________________________________________________________
NOTE: The following files are part of Piotr's Toolbox, and are provided for
convenience only:
fhog.m
gradientMex.cpp
gradientMex.mexa64
gradientMex.mexw64
You are encouraged to get the full version of this excellent library, at which
point they can be safely deleted.
Piotr's Toolbox (3.25) -- http://vision.ucsd.edu/~pdollar/toolbox/doc/index.html
_______________________________________________________________________________
Copyright (c) 2012, Piotr Dollar
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the FreeBSD Project.