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SUMMARY:Algebraic methods in computer vision and automatic generation of e
 fficient algebraic solvers - Zuzana Kukelova\, Center for Machine Percepti
 on/Martin Bujnak\, Capturing Reality s.r.o.
DTSTART:20131118T140000Z
DTEND:20131118T150000Z
UID:TALK48941@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:Many problems in computer vision can be formulated using syste
 ms of polynomial equations. Often\, these systems are not trivial and ther
 efore special algorithms have to be designed to achieve numerical robustne
 ss and computational efficiency when solving them.\nIn the first talk\, pr
 esented by Zuzana Kukelova\, we will briefly discuss two algebraic methods
  for creating such efficient solvers for computer vision problems. One is 
 based on Groebner basis methods for solving systems of polynomial equation
 s and one on polynomial eigenvalue problems and resultants.\nIn the second
  talk\, presented by Martin Bujnak\, we will introduce the automatic gener
 ator of such efficient Groebner basis solvers which could be used even by 
 non-experts to solve problems resulting in systems of polynomial equations
 .\nWe will present several methods for speeding up such solvers based on G
 roebner bases and action matrix eigenvalue computations. \nFinally we will
  show several new solutions to absolute and relative pose problems which w
 e have created using the two presented methods.
LOCATION:Small Lecture Theatre\, Microsoft Research Ltd\, 21 Station Road\
 , Cambridge\, CB1 2FB
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