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【目标追踪】基于核相关滤波器实现目标跟踪含matlab源码

时间:2022-06-20 来源: 浏览:

【目标追踪】基于核相关滤波器实现目标跟踪含matlab源码

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博主简介:擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真,完整matlab代码或者程序定制加qq1575304183。

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1 简介

目标跟踪技术在智能交通、安全监控、人机交互和运动分析等领域有着广泛的应用。近些年,目标跟踪技术取得了飞速的发展,涌现出许多优秀的目标跟踪算法,解决了很多棘手的目标跟踪问题。但是,目标跟踪技术仍然面临着很多的挑战,由于现实环境较为复杂,目前的跟踪算法在实时性、精确性等方面还不能满足实际应用。本文对KCF目标跟踪算法进行优化,KCF跟踪算法利用循环矩阵进行密集采样提取图像的HOG特征,使用正则化最小二乘分类器进行训练提高了运行速度。KCF跟踪算法的优势为目标跟踪速度快,在Benmark视频序列集OTB50的平均速度为172fps,平均精度为73.2%。

2 部分代码

function [img_files, pos , target_sz, ground_truth, video_path] = load_video_info(base_path, video) %LOAD_VIDEO_INFO % Loads all the relevant information for the video in the given path: % the list of image files (cell array of strings), initial position % ( 1 x2), target size ( 1 x2), the ground truth information for precision % calculations (Nx2, for N frames), and the path where the images are % located. The ordering of coordinates and sizes is always [ y , x ]. %在给定路径中加载视频的所有相关信息:图像文件列表(字符串单元数组)、初始位置( 1 x2)、 %目标大小( 1 x2)、用于精确计算的ground truth信息(N帧的Nx2)以及图像所在的路径。 %坐标和大小的顺序总是[ y , x ]。 % % Joao F. Henriques, 2014 % http: //www .isr.uc.pt/~henriques/ %see if there ’s a suffix, specifying one of multiple targets, for %example the dot and number in ’ Jogging. 1 ’ or ’ Jogging. 2 ’. %{ if numel(video) >= 2 && video(end-1) == ’ . ’ && ~isnan(str2double(video(end))), suffix = video(end-1:end); %remember the suffix video = video(1:end-2); %remove it from the video name else suffix = ’ ’; end %full path to the video’ s files if base_path(end) ~= ’/’ && base_path(end) ~= ’’, base_path(end+1) = ’ / ’; end %} %video_path = [base_path video ’ / ’]; %video_path = [base_path video]; % video_path = choose_video(base_path);%大概因为这句,所以我需要选择两次视频 video_path = video; %try to load ground truth from text file (Benchmark’ s format ) %尝试从文本文件(基准测试的格式)加载ground truth %{ filename = [video_path ’Basketball_gt’ suffix ’.txt’ ]; f = fopen(filename); assert(f ~= - 1 , [ ’No initial position or ground truth to load ("’ filename ’").’ ]) %the format is [ x , y , width, height] try ground_truth = textscan(f, ’%f,%f,%f,%f’ , ’ReturnOnError’ ,false); catch %#ok, try different format ( no commas) frewind(f); ground_truth = textscan(f, ’%f %f %f %f’ ); end %} text_files = dir([video_path ’*_gt.txt’ ]); assert(~isempty(text_files), ’No initial position and ground truth (*_gt.txt) to load.’ ) f = fopen([video_path text_files( 1 ).name]); ground_truth = textscan(f, ’%f,%f,%f,%f’ );%已经将car4数据进行修改 ground_truth = cat( 2 , ground_truth{:}); fclose(f); %set initial position and size target_sz = [ground_truth( 1 , 4 ), ground_truth( 1 , 3 )]; pos = [ground_truth( 1 , 2 ), ground_truth( 1 , 1 )] + floor(target_sz/ 2 ); if size(ground_truth, 1 ) == 1 , %we have ground truth for the first frame only (initial position) ground_truth = []; else %store positions instead of boxes ground_truth = ground_truth(:,[ 2 , 1 ]) + ground_truth(:,[ 4 , 3 ]) / 2 ; end %from now on, work in the subfolder where all the images are video_path = [video_path ’imgs/’ ]; %f or these sequences, we must limit ourselves to a range of frames. %for all others, we just load all png/jpg files in the folder. frames = { ’David’ , 300 , 770 ; ’Football1’ , 1 , 74 ; ’Freeman3’ , 1 , 460 ; ’Freeman4’ , 1 , 283 }; idx = find(strcmpi(video, frames(:, 1 ))); if isempty(idx), %general case, just list all images img_files = dir([video_path ’*.png’ ]); if isempty(img_files), img_files = dir([video_path ’*.jpg’ ]); assert(~isempty(img_files), ’No image files to load.’ ) end img_files = sort ({img_files.name}); else %list specified frames. try png first, then jpg. if exist( sprintf ( ’%s%04i.png’ , video_path, frames{idx, 2 }), ’file’ ), img_files = num2str((frames{idx, 2 } : frames{idx, 3 }) ’, ’ %04i.png ’); elseif exist(sprintf(’ %s%04i.jpg ’, video_path, frames{idx,2}), ’ file ’), img_files = num2str((frames{idx,2} : frames{idx,3})’ , ’%04i.jpg’ ); else error( ’No image files to load.’ ) end img_files = cellstr(img_files); end end

3 仿真结果

4 参考文献

[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.

博主简介:擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真,相关matlab代码问题可私信交流。

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