Matching as a non-cooperative game

With this paper we offer a game-theoretic perspective for the all-pervasive matching problem in computer vision. Specifically, we formulate the matching problem as a (population) non-cooperative game where the potential associations between the items to be matched correspond to (pure) strategies, while payoffs reflect the degree of compatibility between competing hypotheses. Within this formulation, the solutions of the matching problem correspond to evolutionary stable states (ESS's), a robust population-based generalization of the notion of a Nash equilibrium. In order to find ESS's of our matching game, we propose using a novel, fast evolutionary game dynamics motivated by Darwinian selection processes, which let the pure strategies play against each other until an equilibrium is reached. A distinguishing feature of the proposed framework is that it allows one to naturally deal with general many-to-many matching problems even in the presence of asymmetric compatibilities....

• Type: Journal
• Year: 2009
• Where: ICCV
• Authors: Andrea Albarelli, Samuel Rota Bulò, Andrea Torsello, Marcello Pelillo
• Keywords: All-pervasive Matching Problem, Computer Vision, ICCV 2009, Many-to-many Matching Problems, Matching Problems