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run_lct2.m
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run_lct2.m
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function results = run_lct2(seq, res_path, bSaveImage)
addpath('./utility');
config.padding = 1.8; %extra area surrounding the target
config.lambda = 1e-4; %regularization
config.output_sigma_factor = 0.1; %spatial bandwidth (proportional to target)
config.interp_factor=0.01; % best 0.01
config.kernel_sigma = 1;
config.features.hog_orientations = 9;
config.features.cell_size = 4; % size of hog grid cell
config.features.window_size = 6; % size of local region for intensity historgram
config.features.nbins=8; % bins of intensity historgram
config.motion_thresh=0.15;
config.appearance_thresh=0.38;
show_visualization=0;
target_sz = [seq.init_rect(1,4), seq.init_rect(1,3)];
pos = [seq.init_rect(1,2), seq.init_rect(1,1)] + floor(target_sz/2);
img_files = seq.s_frames;
video_path='';
[positions, time] = tracker_lct(video_path, img_files, pos, target_sz, config, show_visualization);
%return results to benchmark, in a workspace variable
rects = [positions(:,2) - target_sz(2)/2, positions(:,1) - target_sz(1)/2];
rects(:,3) = target_sz(2);
rects(:,4) = target_sz(1);
res.type = 'rect';
res.res = rects;
res.fps=numel(img_files)/time;
results=res;
end