  Studies on computational neuroscience through functional magnetic resonance
imaging (fMRI) and following biological inspired system stated that human
action recognition in the brain of mammalian leads two distinct pathways in the
model, which are specialized for analysis of motion (optic flow) and form
information. Principally, we have defined a novel and robust form features
applying active basis model as form extractor in form pathway in the biological
inspired model. An unbalanced synergetic neural net-work classifies shapes and
structures of human objects along with tuning its attention parameter by
quantum particle swarm optimization (QPSO) via initiation of Centroidal Voronoi
Tessellations. These tools utilized and justified as strong tools for following
biological system model in form pathway. But the final decision has done by
combination of ultimate outcomes of both pathways via fuzzy inference which
increases novality of proposed model. Combination of these two brain pathways
is done by considering each feature sets in Gaussian membership functions with
fuzzy product inference method. Two configurations have been proposed for form
pathway: applying multi-prototype human action templates using two time
synergetic neural network for obtaining uniform template regarding each
actions, and second scenario that it uses abstracting human action in four
key-frames. Experimental results showed promising accuracy performance on
different datasets (KTH and Weizmann).
