This page contains source programs coded by our laboratory.
They are formatted by “tar” and “gzip”.If you download them, unpack them by “gunzip” and “tar” and follow the instructions described in the README files. All the programs are in the public domain; they do not contain licensed codes or parts of commercial software.
Geometric Computation
Fundamental matrix computation (C++)
This program optimally computes the fundamental matrix from point correspondences between two images. When you unpack the package, a directory named “fundamental” is automatically created. For the details, see README, which will be created in that directory.
Last Update:2003.06.16 correct.c fixed
References:
K. Kanatani,”Optimal fundmamental matrix computation: Algorithm and reliability analysis”,
Proc. 6th Symp. Sensing via Image Information(SSII 2000),June 2000,Yokohama,Japan, pp.291–298.
Flow fundamental matrix computation (C++)
This program optimally computes the flow fundamental matrix from point correspondences between two images regarded as defining optical flow. When you unpack the package, a directory named “flowmat” is automatically created. For the details, see README, which will be created in that directory. zip for windows
References:
K.Kanatani, Y.Shimizu, N.Ohta, M.J.Brooks, W.Chojnacki and A.van der Hengel, “Fundamental matrix from optical flow: Optimal computation and reliability evaluation”,
Journal of Electronic Imaging, Vol.19, No.2(2000),194–202.
Homography computation (C++)
This program optimally computes the flow fundamental matrix from point correspondences between two images regarded as defining optical flow. When you unpack the package, a directory named “flowmat” is automatically created. For the details, see README, which will be created in that directory. To compile this program, you need the library file “matrix“. Download it and set it up before compiling the homography program.
References:
K.Kanatani and N.Ohta, “Accuracy bounds and optimal computation of homography for image mosaicing applications”,
Proceedings of the 7th International Conference on Computer Vision, 20–27 September 1999, Kerkyra, Greece, pp.73–78.
3-D rotation estimation (C++)
This program optimally estimates a 3-D rotation matrix from two sets of corresponding 3-D points. When you unpack the package, a directory named “Rotation” is automatically created. For the details, see README, which will be created in that directory. To compile this program, you need the library file “matrix“. Download it and set it up before compiling the rotation program. Last Update:2010.05.25 Corrected
References:
K.Kanatani and N.Ohta, “Accuracy bounds and optimal computation of homography for image mosaicing applications”,
Proceedings of the 7th International Conference on Computer Vision, 20–27 September 1999, Kerkyra, Greece, pp.73–78.
Conic fitting (C++)
This program optimally fits a conic to given points in two dimensions. When you unpack the package, a directory named “conicest” is automatically created. For the details, see README, which will be created in that directory.
References:
Y.Kanazawa and K.Kanatani, “Optimal conic fitting and reliability evaluation”,
IEICE Transactions on Information and Systems, Vol.E79-D, No.9 (1996), pp.1323–1328.
Image Processing
Background Subtraction (C)
This program executes background subtraction robust to illumination chage. When you unpack the package, a directory named “ImDiff” is automatically created. For the details, see README, which will be created in that directory.
References:
N.Ohta, “A Statistical Approach to Background Subtraction for Surveillance Systems”,
Proc. of ICCV 2001, pp.481-486, Vancouver, Canada.
