AICzechia: Zuzana Kukelova: Methods for Generating Efficient Algebraic Solvers for Computer Vision Problems


Datum / čas
Date(s) - 31.05.
17:00 - 18:00

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Zuzana Kukelova: Methods for Generating Efficient Algebraic Solvers for Computer Vision Problems

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Many problems in computer vision, but also in other fields such as robotics, control design, and economics, can be formulated using systems of polynomial equations. For computer vision problems, general algorithms for solving polynomial systems cannot be efficiently applied. The reasons are twofold – computer vision and robotic applications usually require real-time solutions, or they often solve systems of polynomial equations for a huge number, sometimes even millions, of different instances. Several approaches based on algebraic geometry have been recently proposed for the design of very efficient algorithms (solvers) that solve specific classes of systems of polynomial equations. In this talk, we will briefly discuss the main idea of these methods, which use the structure of the system of polynomial equations representing a particular problem to design an efficient specific solver for this problem. We will also discuss several approaches for improving the efficiency of the final solvers. Finally, we will demonstrate the usefulness of these methods by presenting efficient solutions to several important computer vision problems.


Zuzana Kukelova is an assistant professor at the Czech Technical University in Prague (CTU). She received her PhD from CTU in 2013, and her Master’s in 2005 from Comenius University in Bratislava, Slovakia. She was a Postdoctoral Researcher at Microsoft Research Cambridge (2014-2016). Zuzana is an expert on solving minimal problems in 3D computer vision and methods for generating efficient solvers for systems of polynomial equations. She is the co-author of the first automatic generator of efficient polynomial equation solvers based on Gröbner bases. She has worked on absolute and relative camera pose estimation for (partially) uncalibrated and rolling shutter cameras. Her solvers are part of structure-from-motion, localization, and calibration systems. Zuzana has co-organized tutorials on minimal problems at ICCV’15 and CVPR’19, was an AC for 3DV’18, 3DV’19, ACCV’20, and CVPR’22, a program chair for 3DV’20, and is currently a general chair for 3DV’22.