Authors : Tomas Vojir, Jana Noskova, Jiri Matas
This C++ code implements a tracking pipeline of Scale Adaptive Mean-Shift method.
It is free for research use. If you find it useful or use it in your research, please cite the [1] paper.
The code depends on OpenCV 2.4+ library and is build via cmake toolchain.
Quick start guide
for linux: open terminal in the directory with the code
$ mkdir build; cd build; cmake .. ; make
This code compiles into two binaries demo and asms_vot
./asms_demo
- run live demo with visual output
- control : object is selected by mouse, click and drag mouse to select rectandle
- ESC = quit
- i = init new object
./asms_vot
- using VOT 2015 methodology (http://www.votchallenge.net/), is backward compatible with older ones
- INPUT : expecting two files, images.txt (list of sequence images with absolute path) and region.txt with initial bounding box in the first frame in format "top_left_x, top_left_y, width, height"
- OUTPUT : output.txt containing the bounding boxes in the same format as region.txt
./asms_trax
- using VOT2014+ trax protocol
- require trax library to be compiled with opencv support and installed. See trax instruction for compiling and installing.
References
[1] Tomas Vojir, Jana Noskova and Jiri Matas, “Robust scale-adaptive mean-shift for tracking“. Pattern Recognition Letters 2014.
Copyright (c) 2014, Tomáš Vojíř
Permission to use, copy, modify, and distribute this software for research purposes 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.