Analysis of genetic programming in gait recognition

Analysis of human motion is one of the most curious fields among different disciplines of socio-psychology, neuro biology and computer science. A person´s walk is so crucial because it is associated with lots of other aspects which yield very important information related to emotions, personality, and neurological disorder. The morphological and psychological information induced from both the physiology and neurology involved in motion is one of the key research fields that could one day resolve the various challenges existing in today´s intelligent systems inspired from nature. The most interesting among all these is, those wealth of data can be artificially trained using the complex systems in response to generate evidences for identifying the particular person [1]. This paper is the extension of human gait recognition which presents the analysis of efficiency of genetic programming in different cases involved in feature extraction and gait recognition.