photoscanも結構豊富に作れて早いのだが
ここは細かな点群を調整する意味でcloudcompareを使う

メッシュを作成後、必要とする何かと言うと画面上の緑の部分
これデータが無いけどどうしても作られてしまう
It is too early to make photoscan fairly abundantly
Here, use cloudcompare to adjust fine point clouds

After creating the mesh, something you need to say is the green part on the screen
It would be made anyway but this data is not

octree depth 11
続きを読む cloudcompare:メッシュの作成 必要なデータにする →

photoscanも結構豊富に作れて早いのだが
ここは細かな点群を調整する意味でcloudcompareを使う

ようやくメッシュ化
Plugins >> Poisson Recon
photoscan also fast to it and make quite rich, but here use the cloudcompare in the sense to adjust the fine point cloud

Finally mesh
Plugins >> Poisson Recon

設定は、ざっくりでoctree depth
Settings roughly octree depth

こんなかんじ！
わかるかって思えば、とりあえず

octree depth 11ぐらいから
like this!
If you think I You know, for the time being

About octree depth 11

結構きれいだけど、フラットすぎるので、
時間的に、2分ぐらいかな？

octree depth 15ぐらいから
It’s pretty beautiful but it’s too flat,
Temporally, about 2 minutes?

About octree depth 15

時間的に、30分ぐらいかな？
ようやく形状が見えてきたぐらい

データ数は、これだけで84,314,786 triangles,42,157,487 verticesですと。
Temporally, about 30 minutes or so?
At last the shape is about to be visible

The number of data, this alone 84,314,786 triangles, and is 42,157,487 vertices.

メッシュの容量が、4G以上になったまだ終了しない
莫大な時間も必須ですね。
11ぐらいが無難かと。
Mesh capacity has reached 4 G or more It does not finish yet
It is also required enormous time.
About 11 safe or with.

photoscanも結構豊富に作れて早いのだが、ここは細かな点群を調整する意味でcloudcompareを使う
これも手順が必要
まず、
メッシュ化に前に不要な点群を間引く
photoscan also fast to it and make quite rich, but here use the cloudcompare in the sense to adjust the fine point cloud
This also requires a procedure
First,
Decimating unnecessary point cloud before the meshing

Edit >> Subsamples
不整形三角網の平均化だねきっと。
三角網の平均化で同じような近傍点で細かな三角網はいらないって事かな。
Edit >> Subsamples
It is the averaging of the irregular triangle net surely.
I wonder if a triangular mesh is averaged and you do not need a fine triangle at similar neighbor points.

planeが最適
plane is optimal

quadric

Trianglation
続きを読む cloudcompare:メッシュの作成 点群を間引く →