English
资源说明：Abstract
Estimating relative camera motion from two views is a
classical problem in computer vision. The minimal case for
such problem is the so-called five-point-problem, for which
the state-of-the-art solution is Nist´er’s algorithm [9]. However,
due to the heuristic and ad hoc nature of the procedures
it applies, to implement it is not so easy for non-expert
users. This paper provides a much easier algorithm based
on hidden variable resultant technique. Instead of eliminating
the unknown variables one by one (i.e., sequentially)
using the Gaussian method as in [9], our algorithm eliminates
many unknowns all at once. Moreover, in the equation
solving stage, instead of back-substituting and solve all the
unknowns sequentially, we compute the minimal singular
vector of the coefficient matrix, by which all the unknown
parameters can be estimated simultaneously. Experiments
on both simulation and real images have validated the new
algorithm.
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