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【辅助驾驶】KITTI激光数据与图像数据的融合MATLAB实现[4]——稠密深度图实现

【辅助驾驶】KITTI激光数据与图像数据的融合MATLAB实现

[4]——稠密深度图实现

⼀、实现效果

⼆、思路与代码

由于激光点云数据⽐较稀疏，直接将激光雷达数据映射到图像上，会有很多点不匹配，对于缺失的深度信息，可以通过周围点的深度的权重进⾏填充。

% Written by Muhammet Balcilar, France

clear all

%close all

clc

I=imread('data/image_2/0000000001.png');

% read calibration file

fd = fopen('data/');

raw_data = fscanf(fd,'%c');

fclose(fd);

ii = find(raw_data == ':')+1;

ie = find(raw_data == 10 );

P0 = reshape(str2num( raw_data(ii(1):ie(1)) ),4,3)';

P1 = reshape(str2num( raw_data(ii(2):ie(2)) ),4,3)';

P2 = reshape(str2num( raw_data(ii(3):ie(3)) ),4,3)';

P3 = reshape(str2num( raw_data(ii(4):ie(4)) ),4,3)';

R0_rect = reshape(str2num( raw_data(ii(5):ie(5)) ),3,3)';

Tr_velo_to_cam = reshape(str2num( raw_data(ii(6):ie(6)) ),4,3)';

Tr_imu_to_velo = reshape(str2num( raw_data(ii(7):ie(7)) ),4,3)';

% read Lidar data file

fd = fopen('data/velodyne/0000000001.bin','rb');

velo = fread(fd,[4 inf],'single')';

fclose(fd);

% remove all points behind image plane (approximation)

idx = velo(:,1)<5;

velo(idx,:) = [];

% exclude luminance make last column all 1

velo(:,4)=1;

% draw raw point cloud

figure;

plot3(velo(:,1),velo(:,2),velo(:,3),'r.');

title('Raw point Cloud');

% create projection matrix

R0_rect(4,4)=1;

Tr_velo_to_cam(4,4)=1;

P=P2 * R0_rect * Tr_velo_to_cam;

% project to image plane

px = (P * velo')';

px(:,1) = px(:,1)./px(:,3);

px(:,2) = px(:,2)./px(:,3);

% remove out of image size indexes

px(px(:,1)<1,:)=[];

px(px(:,1)>size(I,2),:)=[];

px(px(:,2)>size(I,1),:)=[];

[n m k]=size(I);

tic

[fulldepth depth] =dense_depth_map(px,n, m,4);

toc

figure;imagesc(fulldepth,[0 30]);

axis image

axis off

title('Full Depth map grid=4');

figure;imagesc(depth);

axis image

axis off

title('Initial Depth map');

% Composite image of grayscale left image and disparity map tmp(:,:,1) = double(rgb2gray(I))/255;

tmp(:,:,2) =tmp(:,:,1);

tmp(:,:,3) =tmp(:,:,1);

dmap=1./fulldepth;

dmap(isinf(dmap))=0;

dmap=63*(dmap-min(dmap(:)))./(max(dmap(:))-min(dmap(:))); dmap=round(dmap);

figure;sc= colormap('jet');

DImage = 0.5*tmp + 0.5*reshape(sc(dmap+1,:), [n,m ,3]); imshow((DImage));title('Inverse of Depth');

三、项⽬下载

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