Kenichi Kanatani received his B.E., M.S., and Ph.D. in applied mathematics from the University of Tokyo in 1972, 1974, and 1979, respectively. After serving as Professor of computer science at Gunma University, Gunma, Japan, and Okayama University, Okayama, Japan, he retired in 2013 and is now Professor Emeritus of Okayama University. He was a visiting researcher at the University of Maryland, U.S. (1985–1986, 1988–1989, 1992), the University of Copenhagen, Denmark (1988), the University of Oxford, U.K. (1991), INRIA at Rhone Alpes, France (1988), ETH, Switzerland (2013), University of Paris-Est, France (2014), Linkoping University, Sweden (2015), and National Taiwan Normal University, Taiwan (2019). He is the author of K. Kanatani, Group-Theoretical Methods in Image Understanding (Springer, 1990), K. Kanatani, Geometric Computation for Machine Vision (Oxford University Press, 1993), K. Kanatani, Statistical Optimization for Geometric Computation: Theory and Practice (Elsevier, 1996; reprinted Dover, 2005), K. Kanatani, Understanding Geometric Algebra: Hamilton, Grassmann, and Clifford for Computer Vision and Graphics (AK Peters/CRC Press 2015), K. Kanatani, Y. Sugaya, and Y. Kanazawa, Ellipse Fitting for Computer Vision: Implementation and Applications (Morgan & Claypool, 2016). K. Kanatani, Y. Sugaya, and Y. Kanazawa, Guide to 3D Vision Computation: Geometric Analysis and Implementation (Springer, 2016), and K. Kanatani, 3D Rotations: Parameter Computation and Lie Algebra based Optimization (AK Peters/CRC Press 2020). He received many awards including the best paper awards from IPSJ (1987), IEICE (2005), and PSIVT (2009). He is a Fellow of IEICE, IEEE, and IAPR.
