Title :
Human posture estimation from multiple images using genetic algorithm
Author :
Ohya, Jun ; Kishino, Fumio
Author_Institution :
ATR Commun. Syst. Res. Labs., Kyoto, Japan
Abstract :
A new method for estimating human postures at a time instant from multiple images using a genetic algorithm is proposed. The posture parameters to be estimated are assigned to the genes of individuals in the population. For each individual, its fitness evaluates to what extent the multiple human images synthesized by deforming a 3D human model according to the values of the genes are registered to the real multiple human images. Genetic operations such as natural selection, crossover and mutation are performed, and individuals in the next generation are generated. After a certain number of repetitions for these processes, the estimated parameter values are obtained from the individual with the best fitness. Experiments using synthesized human multiple images show promising results
Keywords :
image recognition; 3D human model; best fitness; crossover; genetic algorithm; human posture estimation; multiple images; mutation; natural selection; Deformable models; Genetic algorithms; Genetic mutations; Humans; Joints; Laboratories; Layout; Motion analysis; Parameter estimation; Visual communication;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576430