Eventhough the aim of the study is to recognize the human beings in the images from monocular camera without usual constraints, initially the graph theory based methods for matching are analyzed with new neighbour isomorphism. The robust Hausdorff method of matching is extended to recognize the human beings with ample models and modified distance measures. As the strategy to fuse different algorithms to get better results despite occlusions is inherently parallel, the parallel implementations on Cray T3E produced correct results in appreciably shorter computation time. As industrial applications in robotics, three example situations, one with known environment, another with unknown environment and the third with going around were discussed taking primitive models with human beings as obstacles. Unless the problem of choosing a proper model with the good indexing is available, the recognition of human beings will continue to remain as one of the hard problems to be solved.