Model-based Estimation of Human Posture Parameters from Multiple Camera Images Using Genetic Algorithms

Abstract

A new method for estimating human posture from multiple images using a genetic algorithm is proposed. In the proposed algorithm, the posture parameters to be estimated are assigned to the genes of an individual in the population. For each individual, its fitness evaluates to what extent the human multiple images synthesized by deforming a 3D human model according to the values of the genes are registered to the real human multiple images. Genetic operations such as natural selection, crossover and mutation are performed so that individuals in the next generation are generated. After a certain number of repetitions of these processes, the estimated parameter values are obtained from the individual with the best fitness. Experiments using multiple synthesized images show promising results for estimating 17 joint angle values for each degree of freedom of the joints and also the three translational and three rotational degrees of freedom.