Human posture estimation from multiple images using genetic algorithm

Jun Ohya, Fumio Kishino

Research output: Contribution to journalConference articlepeer-review

35 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)750-753
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Publication statusPublished - 1994
Externally publishedYes
EventProceedings of the 12th IAPR International Conference on Pattern Recognition. Part 1 (of 3) - Jerusalem, Isr
Duration: 1994 Oct 91994 Oct 13

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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