The following instruciton is too old. Now it takes point cloud files instead of txt files. Please see src/main.cpp for more detail.
CUDA-based implementations of Softassign and EM-ICP, CVPR2010 Demo http://home.hiroshima-u.ac.jp/tamaki/study/cuda_softassign_emicp/
Toru Tamaki, Miho Abe, Bisser Raytchev, Kazufumi Kaneda, Marcos Slomp (Hiroshima University, Japan) Contact address: [email protected]
Wed Aug 27 19:11:45 JST 2014
- CUDA 6.5
- PCL 1.7
- FLANN
- Boost
- lapack, blas
cuda_emicp_softassign [options]
This demo application finds R and t such that min ||X - (R*Y+t) || for given 3D point sets X and Y.
At the start, the demo application popups a window where two point sets are shown.
$ ./build/cuda_emicp_softassign -pointFileX=./data/P101.txt -Xsize=101 -pointFileY=./data/Qnew101.txt -Ysize=101 -emicp
This aligns P101.txt and Qnew101.txt (both of 101 points) by using EM-ICP.
$ ./build/cuda_emicp_softassign -ply -pointFileX=./data/bun000.ply -pointFileY=./data/bun045.ply -pointsReductionRate=5 -softassign
This aligns bun000.ply and bun045.ply by using Softassign. Numbers of points in both point sets are reduced (randomly approximately) 5% of its original numbers.
$ make -f Makefile.demo demo
-pointFileX=filename
-pointFileY=filename
[string] Filename of two 3D point sets. Requred.
Format of file: in each line, x y z coordinates are stored. That’s all. Number of points are specified with Xsize and Ysize options.
-pointsReductionRate=**
[float] Numbers of points in the files are randomlyl reduced to ** % (approximately). default: no reduction.
-pointsReductionRateX=**
[float] Numbers of points X in the files are randomlyl reduced to ** % (approximately). default: no reduction.
-pointsReductionRateY=**
[float] Numbers of points Y in the files are randomlyl reduced to ** % (approximately). default: no reduction.
Example: -pointsReductionRate=10 then the number of points is reduced to about 10%.
Note: if -pointsReductionRate exists, -pointsReductionRate{X,Y} are ignored.
[-icp | -emicp | -emicpcpu | -softassign]
Choose one of these. default: -softassign is assumed.
-JMAX=***
[int] Number of iterations for the annealing loop (1st loop). At first, the annealing temprature T is set to T_0, then T <- T*TFACOR at the end of each iteration. default: 100
-I0=***
[int] Number of iterations with the same temprature (2nd loop). default: 5
-I1=***
[int] Number of iterations for Shinkhorn’s row/column normalizations. default: 3
-alpha=***
[float] parameter for outliers (see the original Softassign paper). default: 3.0
-T_0=***
[float] initial temprature for the annealing process. default: 100.0
-TFACTOR=***
[float] factor for reducing temprature. default: 0.95
-moutlier=***
[float] values of elements in the extra row/column for outliers (see the original Softassign paper). default: 1/sqrtf(T_0)*expf(-1.0f)
-maxIteration=***
[int] Number of ICP iterations. default: 30
-sigma_p2=***
[float] initial value for the main loop. sigma_p2 <- sigma_p2 * sigma_factor at the end of each iteration while sigma_p2 > sigam_inf. default: 0.01
-sigma_inf=***
[float] minimum value of sigma_p2. default: 0.00001
-sigma_factor=***
[float] facfor for reducing sigma_p2. default: 0.9
-d_02=***
[float] values for outlier (see EM-ICP paper). default: 0.01
-noviewer
No viewer is shown. Just align point sets, and quit.
-notimer
No timer is shown.
-nostop
No interatction by the viewer is required.
-saveRTtoFile=filename
save the estimated rotation matrix and translation vector. default: nothing saved.
-loadRTfromFile=filename
load initial values for rotation matrix R and translation vector t. default: no values are loaded, and set R=3x3 identity matrix, t=zero vector.
Save and load format: R and t are stored in row-wise.
r11 r12 r13
r21 r22 r23
r31 r32 r33
tx ty tz
-alignScaleOnce
two point clouds are aligned in scales at the beginning.
testd on Ubunts 14.04LTS
sudo apt-get install libpcl-1.7-all-dev libflann-dev libboost-all-dev ccache libatlas-dev libblas-dev liblapack-dev cmake
mkdir build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_VERBOSE_MAKEFILE=1 ..
void icp(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_targetX,
const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_sourceY,float* h_R, float* h_t, registrationParameters param)
void softassign(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_targetX,
const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_sourceY, float* h_R, float* h_t, registrationParameters param)
void emicp(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_targetX,
const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_sourceY,float* h_R, float* h_t, registrationParameters param)
void emicpcpu(const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_targetX,
const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_sourceY,float* h_R, float* h_t, registrationParameters param)
To use these functions,
compile your program with either icp.cpp, softassign.cu, emicp.cu, or emicp_cpu.cpp along with 3dregistration.h.
cloud_targetX, cloud_sourceY [Input]
Specify the pointers to pcl::PointCloud storing point sets X and Y.
float* h_R, float* h_t [Input/Output]
- On entry, initial values for rotation matrix R and translation vector t must be given. Usually, R=3x3 identity matrix, t=zero vector.
- On exit, estimated R and t are stored.
- Order of elements:
h_R[0], ..., h_R[8]: r11 r12 r13 r21 r22 r23 r31 r32 r33
h_t[0], ..., h_t[2] : tx,ty,tz
registrationParameters param [Input]
parameters for alignment. set values by yourself. see 3dregistration.h and usage of demo (described above).
If you do not use the viewer, define
#define NOVIEWER
when compling icp.cpp, softassign.cu, emicp.cu, or emicp_cpu.cpp.
/*
Copyright (c) 2010 Toru Tamaki
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
*/
We kindly ask for users to refer
- Toru Tamaki, Miho Abe, Bisser Raytchev, Kazufumi Kaneda, Marcos Slomp, "CUDA-based implementations of Softassign and EM-ICP," CVPR2010 Demo, 2009.
- Toru Tamaki, Miho Abe, Bisser Raytchev, Kazufumi Kaneda: "Softassign and EM-ICP on GPU", Proc. of The 2nd Workshop on Ultra Performance and Dependable Acceleration Systems (UPDAS), CD-ROM, 5 pages, 2010. http://dx.doi.org/10.1109/IC-NC.2010.60
in your paper publised by using our implementation. Thank you!
Dataset used in this demonstration is taken from the following website:
- The Stanford Bunny, Stanford University Computer Graphics Laboratory, The Stanford 3D Scanning Repository. http://graphics.stanford.edu/data/3Dscanrep/