Sparse resultant-based methods with their applications to generalized cameras

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

L10, Linnanmaa

Topic of the dissertation

Sparse resultant-based methods with their applications to generalized cameras

Doctoral candidate

Master of Science (Tech.) Snehal Bhayani

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Center for Machine Vision and Signal Analysis

Subject of study

Geometric computer vision


Professor Kalle Åström, Lund University


Professor Janne Heikkilä, University of Oulu

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Novel algorithms for solving polynomial equations in computer vision

Finding the solutions of a set of equations is a classical problem in mathematics, with a rich literature. Recently, these mathematical techniques have gained popularity in various fields of computer science, specifically computer vision and robotics. This thesis proposes novel algorithms to efficiently solve the equations, specifically arising in computer vision. The algorithms borrow concepts from algebra and geometry, and are implemented as easy-to-use software programs. Further, the thesis also studies the challenging problems involving multi-camera systems and solves them using the proposed algorithms. The multi-camera systems are important in applications such as autonomous driving, SLAM (simultaneous localization and mapping), 3D reconstruction, etc.
Last updated: 13.11.2023