Abstract
Human motion has already deeply affected many aspects of psychological and social research. On the other hand, because of the huge challenges and new dimensions of its increasingly extreme applications, this field remains an inspiring area in which to explore rich possibilities in the fields of artificial intelligence and bio-informatics. In this research, we investigated a novel approach to identify individuals based on their gaits. Furthermore, we investigated a new avenue of the research toward the biometric identification of humans that involves the classification of human gait using the power of genetic programming (GP). Moreover, we also propose an approach that applies collaborative filter using multiple evolved classifiers to address the challenges of non-determinism and insufficient generality of GP.
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Sharma, D.G., Yusuf, R., Tanev, I. et al. Human gait analysis based on biological motion and evolutionary computing. Artif Life Robotics 21, 188–194 (2016). https://doi.org/10.1007/s10015-016-0267-8
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DOI: https://doi.org/10.1007/s10015-016-0267-8