Tomas Pajdla
Associate Professor & Distinguished Researcher, Leader of AAG Group AAG  Applied Algebra & Geometry Group Czech Institute of Informatics, Robotics and Cybernetics Czech
Technical University in Prague National
Institute of Informatics, Tokyo 




News 







2018 September  December Visiting ICERM @ Brown University 2018 September 2018 June 2018 March 
Interests 
Computer Vision, Machine Learning, Robotics, Geometry, Algebra, Optimization 

Papers 

Talks 
Algebraic Geometry & 3D Reconstruction @ ISPRS 2016, Solving Minimal Problems in Computer Vision Tutorial @ ICCV 2015, Omnidirectional Vision Course @ ICCV 2003, Stereo Geometries of Noncentral Cameras 2001 

Teaching 
Geometry of Computer Vision and Computer Graphics (CTU in Prague), Advanced Robotics (CTU in Prague), Geometry of Computer Vision (Charles University in Prague), Geometry of Computer Vision (Ukrainian Catholic University in Lviv) 

Links 




Automatic Generator of Minimal Solvers CMP
SfM Webservice GpoSolver – Global Polynom Optimization radhomo0.1 – Rad Dist Homogrphy [pdf] F100.1 – Rad Relative Pose [pdf] bbhec – BB HandEye Optimization mpherwc – HandEye & RW Cal [pdf] minhec – HandEye Cal Minimal [pdf] polyopt – Polynom Opt by SDP Relax TEinversion – Uncertainty propag in SfM


2017 IMPACT Project (EU & MSMT)

Research topics for PhD, MSc and BSc students. 


3D Scene Reconstruction from Images 3D scene reconstruction from images is a fundamental problem of
computer vision. It finds many applications in industry ranging from
autonomous driving to movie special effects. The topic is best for students
with interest in algorithms, experimental work, and engineering of really
working systems. Algebraic techniques have proved very useful in solving
difficult problems in geometry of computer vision. We will aim at studying
more advanced elements of algebraic geometry and applying them to real
engineering problems. The topic is best for students with interest in applied
mathematics. Visual scene recognition and image based localization is an important problem in computer vision and machine learning. We will aim developing new approaches to place representation and its search. The topic is suitable for students with interest computer vision and machine learning applied to real engineering problems. Polynomial Optimization in Computer Vision and Robotics Polynomial optimization techniques proved very useful in solving interesting problems in geometry of computer vision and robotics. We will aim at studying more polynomial optimization techniques and applying them in computer vision and robotics. The topic is suitable for students with interest in applied mathematics but used on real engineering problems. 


2017 September Continental project, 2017 September PC of 3DV 2018, 2017 July J Heller received CSKI Prize 4 his PhD, 2017 July 3 Papers @ CVPR 2017, 2017 June IMPACT project with INRIA started, 2017 May MAGIK Eye – CTU Common Lab founded, 2016 November PC of ACCV 2020, June 2016 3 papers @ CVPR 2016, June 2015 3 papers @ CVPR 2015, January 2015 LADIO EU Project starts. 


©Tomas Pajdla 20172018 