Optimal geometric model matching under full 3D perspective

Matching algorithms use random-start local search and a 3D pose recovery algorithm to find optimal matches between 3D object models and 2D image features. An algorithm using only a a weak-perspective approximation to full 3D perspective solves a subset of the test problems presented. A second algorithm always uses an iterative 3D pose algorithm to account for 3D perspective and solves all test problems including those with varying 3D perspective. A third hybrid algorithm uses weak-perspective to direct search and 3D pose to periodically correct for perspective. It is faster than the second. A fourth algorithm is a hybrid which also uses a technique called 'subset-convergence ' to escape from some local optima. It performs best on the most difficult matching problems. >