Hybrid symbiotic genetic optimisation for robust edge-based stereo correspondence

This work proposes a novel algorithm for performing robust feature-based stereo-matching, without the ordering constraint. The calculation of the disparity map is decomposed to a set of disjoint intra-row subproblems, each one having two objectives: the search for a high confidence intra-row matching and the enforcement of figural continuity at the inter-row level. A separate genetic algorithm (GA) is allocated at each epipolar to search the feasible solution space. All GAs evolve parallely in a symbiotic fashion and continuously exchange currently available solution information to enable optimisation of figural continuity. To accelerate the search, we adapt a deterministic solver to seed tha GAs and design problem-specific genetic operators for greater efficiency.