%%?點云的配準
clc;
clear;
close?all;

%%?導入數據
dataFile?=?fullfile（toolboxdir（‘vision‘）?‘visiondata‘?‘livingRoom.mat‘）;
load（dataFile）;

%%?依次將點云數據存出來
for?i=1:length（livingRoomData）
????pcwrite（livingRoomData{i}[‘house_init‘num2str（i）]‘PLYFormat‘‘binary‘）;
end

%%?參考點云數據
%?Extract?two?consecutive?point?clouds?and?use?the?first?point?cloud?as
%?reference.
ptCloudRef?=?livingRoomData{1};
ptCloudCurrent?=?livingRoomData{2};

%%?顯示點云
figure;
pcshow（ptCloudRef）;
figure;
pcshow（ptCloudCurrent）;

%%?點云的預處理
%?Note?that?the?downsampling?step?does?not?only?speed?up?the?registration
%?but?can?also?improve?the?accuracy.
gridSize?=?0.1;
fixed?=?pcdownsample（ptCloudRef?‘gridAverage‘?gridSize）;
moving?=?pcdownsample（ptCloudCurrent?‘gridAverage‘?gridSize）;

%%?確定點云之間的變換關系
%?finding?the?rigid?transformation?for?aligning?the?second?point?cloud?with?the?first?point?cloud.
tform?=?pcregrigid（moving?fixed?‘Metric‘‘pointToPlane‘‘Extrapolate‘?true）;
ptCloudAligned?=?pctransform（ptCloudCurrenttform）;

%%?點云的融合
%The?overlapped?region?is?filtered?using?a?1.5cm?box?grid?filter.?
%Increase?the?merge?size?to?reduce?the?storage?requirement?of?the?
%resulting?scene?point?cloud?and?decrease?th