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Human gait analysis based on biological motion and evolutionary computing

机译:基于生物运动和进化计算的人体步态分析

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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 bio-metric 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.
机译:人体运动已经深刻影响了心理学和社会研究的许多方面。另一方面,由于其日益极端的应用面临的巨大挑战和新领域,该领域仍然是一个鼓舞人心的领域,可以在其中探索人工智能和生物信息学领域的丰富可能性。在这项研究中,我们研究了一种基于步态识别个人的新颖方法。此外,我们研究了人类生物特征识别研究的新途径,其中涉及利用基因编程(GP)的力量对步态进行分类。此外,我们还提出了一种方法,该方法使用多个演化分类器应用协作过滤器来解决GP的不确定性和通用性不足的挑战。

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