A Fully Projective Formulation for Lowe's Tracking Algorithm
Helder Jesus Araújo, Rodrigo L. Carceroni, Christopher C. Brown · UR Research (University of Rochester) · 1996
David Lowe's influential and classic algorithm for tracking objects with known geometry is formulated with certain simplifying assumptions. A version implemented by Ishii et al. makes different simplifying assumptions. We formulate a full projective solution and apply the same algorithm (Newton's method). We report results of extensive testing of these three algorithms. We compute two image--space and six pose--space error metrics to quantify the effects of object pose, errors in initial solutions, and image noise levels. We consider several scenaria, from relatively unconstrained conditions to those that mirror real--world and real--time constraints. The conclusion is that the full projective formulation makes the algorithm orders of magnitude more accurate and gives it super--exponential convergence properties with arguably better computation--time properties.