Model-based pose estimation using genetic algorithm

In this paper, we propose a method of the model-based pose estimation in the 3D world from a 2D image. This process consists in searching for the best value of coordinates (x, y, z) and of rotating angles (θ_x, θ_y, θ_z) in which the model object matches most exactly the given input edge image. Taking the match of objects as an index on the six-parameter space, this process can be regarded as a maximum searching problem. We use a genetic algorithm in the estimation of those parameters, and propose a new concept of fitness which takes edge direction into consideration. Our experiments show the results of the proposed method on edge input images