| Summary: | 碩士 === 國立臺中科技大學 === 資訊工程系碩士班 === 100 === The image recognition vigorous development of human gait information is one of the most inevitable trends. This paper proposes two gait recognition research topics. First, the aging recognition benefits the development of social and medical technology development. Therefore, smart home care becomes a focus of attention. This research provides the gesture recognition by using the gait information of the elderly living alone, it’s important of the management of their home safety. Second, the gender recognition provides some important clues for the appropriate service information. The gender recognition can improve the effect of value-added information services, and becomes an important research topic.
A low computational complexity of algorithms has been proposed in this research of home gait recognition cares. Using the rule of triangular shape, the abnormal movements of human body can be detected quickly. The abnormal movement of the elderly living alone can be detected and recognized immediately by a video camera. The accuracy of the successful detection and recognition is 90% in the experiment.
In the aging recognition research, we present a preliminary design and experimental results of gender recognition from walking movements that utilizes gait energy image (GEI) with denoised energy image (DEI) pre-processing as support vector machine (SVM) classifier to training and extract the characteristics. The result shows that the proposed method would adopt the few characteristic value but the accuracy can reach to 100% on the same shot angles and more than 80% on the tolerance of 18 degree shot angles.
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