Readme.txt

1. Download the VGG-NET-19 mat file and put into the model folder using the link
https://uofi.box.com/shared/static/kxzjhbagd6ih1rf7mjyoxn2hy70hltpl.mat

or using the link if you are in China
http://pan.baidu.com/s/1kU1Me5T 

Note that this mat file is compatile with the MatConvNet-1beta10 used in this work, if you download the mat file from
http://www.vlfeat.org/matconvnet/models/imagenet-vgg-verydeep-19.mat,
please pay attention to the version compatibility.  

2. Include the path of matconvnet/matlab

3. Run the main entry file run_tracker.m

% Note that RUN_CF2 is an interfance for OBT-50 and OBT-100:
%
% process a sequence using CF2 (Correlation filter tracking with convolutional features)
%
% Input:
%     - seq:        sequence name
%     - res_path:   result path
%     - bSaveImage: flag for saving images
% Output:
%     - results: tracking results, position prediction over time
%
%   It is provided for educational/researrch purpose only.
%   If you find the software useful, please consider cite our paper.
%
%   Hierarchical Convolutional Features for Visual Tracking
%   Chao Ma, Jia-Bin Huang, Xiaokang Yang, and Ming-Hsuan Yang
%   IEEE International Conference on Computer Vision, ICCV 2015
%
% Contact:
%   Chao Ma (chaoma99@gmail.com), or
%   Jia-Bin Huang (jbhuang1@illinois.edu).