This package contains the source code to reproduce the experimental results of LSART. The source code is mainly written in MATLAB with a modifed Caffe framework.

• Supported OS: the source code was tested on 64-bit Ubuntu 14.04 Linux OS, and it should also be executable in other linux distributions.

• Dependencies:

• A modified version of caffe framework (included in the ./LSART/caffe folder) and all its dependencies.

• Cuda enabled GPUs

• Installation:

1. Install caffe: we use a modified version of the original caffe framework. Compile the source code in the ./LSART/caffe directory and the matlab interface following the installation instruction of caffe. Compile the Matconvnet by running ./LSART/matconvnet/matlab/vl_compilenn.m.
2. Download the 16-layer VGG network from https://gist.github.com/ksimonyan/211839e770f7b538e2d8, and put the caffemodel file under the ./LSART/model directory.
3. Download the VGG-M network (imagenet-vgg-m-2048) from http://www.vlfeat.org/matconvnet/pretrained/, and put the mat file under the ./LSART/networks directory. Note that we do not use the VGG-M as the feature of our tracker. We need VGG-M model to make the feature extraction code of CCOT executable.
4. Properly configure the code (see blow), and run ./vot-toolkit-master/wworkspace/run_experiments.m

(1) In ./LSART/set_tracker_param.m: change Line 1 to use_gpu=0;

(1). In ./LSART/set_tracker_param.m: change Line 3 to "addpath('$CODE_ROOT/LSART/caffe/matlab/', '$CODE_ROOT/LSART/util');" (2). In ./LSART/set_tracker_param.m: change Line 5 to "addpath('$CODE_ROOT/LSART/BBR');" (3). In ./LSART/set_tracker_param.m: change Line 6 to "addpath(genpath('$CODE_ROOT/LSART/matconvnet'));" (4). In ./LSART/set_tracker_param.m: change Line 7 to "addpath(genpath('$CODE_ROOT/LSART/pdollar_toolbox'));" (5). In ./LSART/set_tracker_param.m: change Line 8 to "addpath('$CODE_ROOT/LSART/feature_extraction');" (6). In ./LSART/set_tracker_param.m: change Line 9 to "addpath(genpath('$CODE_ROOT/LSART/ccot_runfile'));" (7). In ./LSART/set_tracker_param.m: change Line 63 to "feature_solver_def_file = '$CODE_ROOT/LSART/model/feature_solver.prototxt';" (8). In ./LSART/set_tracker_param.m: change Line 64 to "model_file = '$CODE_ROOT/LSART/model/VGG_ILSVRC_16_layers.caffemodel';" (9). In ./LSART/set_tracker_param.m: change Line 68 to "feature_solver_def_file1 = 'CODE_ROOT/LSART/model/feature_solver1.prototxt';" (10). In ./LSART/set_tracker_param.m: change Line 69 to "model_file1 = '$CODE_ROOT/LSART/model/VGG_ILSVRC_16_layers.caffemodel';" (11). In ./LSART/set_tracker_param.m: change Line 74 to "spn_solver_def_file = '$CODE_ROOT/LSART/model/spn_solver.prototxt'; " (12). In ./LSART/set_tracker_param.m: change Line 77 to "cnna_solver_def_file = '$CODE_ROOT/LSART/model/cnn-a_solver.prototxt';" (13). In ./LSART/set_tracker_param.m: change Line 80 to "cnnb_solver_def_file = '$CODE_ROOT/LSART/model/cnn-b_solver.prototxt';" (14). In ./LSART/set_tracker_param.m: change Line 83 to "cnn_my_solver_def_file = '$CODE_ROOT/LSART/model/cnn-my_solver.prototxt';" (15). In ./LSART/set_tracker_param.m: change Line 86 to "dtpooling_solver_def_file = '$CODE_ROOT/LSART/model/dtpooling_solver.prototxt';" (16). In ./LSART/set_tracker_param.m: change Line 89 to "KRR_solver_def_file = '$CODE_ROOT/LSART/model/cnn-KRR_solver.prototxt';" (17). In ./LSART/set_tracker_param.m: change Line 92 to "cnnc_solver_def_file = '$CODE_ROOT/LSART/model/cnn-c_solver.prototxt';" (18). In ./LSART/feature_extraction/get_table_feature.m: change Line 24 to "tables{end+1} = load(['$CODE_ROOT/LSART/feature_extraction/lookup_tables/' fparam.tablename]);" (19). In ./LSART/feature_extraction/init_features.m: change Line 60 to "table = load(['$CODE_ROOT/LSART/feature_extraction/lookup_tables/' features{k}.fparams.tablename]);" (20). In ./LSART/feature_extraction/load_cnn.m: change Line 3 to "net = load(['$CODE_ROOT/LSART/networks/' fparams.nn_name]);" (21). In ./LSART/model/cnn-KRR_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/cnn-KRR.prototxt' (22). In ./LSART/model/cnn-a_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/cnn-a.prototxt' (23). In ./LSART/model/cnn-b_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/cnn-b.prototxt' (24). In ./LSART/model/cnn-c_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/cnn-c.prototxt' (25). In ./LSART/model/cnn-my_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/cnn-my.prototxt' (26). In ./LSART/model/dtpooling_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/dtpooling.prototxt' (27). In ./LSART/model/feature_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/feature_net.prototxt' (28). In ./LSART/model/feature_solver1.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/feature_net1.prototxt' (29). In ./LSART/model/spn_solver.prototxt: change Line 1 to net: '$CODE_ROOT/LSART/model/spn.prototxt' We suggest the users to use tools (e.g., cscope) for bulk changes.

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