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 Real-time Video-based Fall Detection using Motion Gradients and Shape Features
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Tác giả hoặc Nhóm tác giả: Huỳnh Hữu Hưng, Nguyễn Trọng Nguyên, Jean Meunier
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Nơi đăng: The 12th IEEE International Symposium on Signal Processing and Information Technology, (ISSPIT 2012)
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; Số: 1;Từ->đến trang: 217-222;Năm: 2012
Lĩnh vực: Công nghệ thông tin; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Fall is a condition occurring very common in the aged population and increases their risk of unnatural death. If the fall is detected early and alerted, we can timely support. Therefore, many fall detection systems have been developed. However, most of them cannot discriminate against real fall and normal motions of human, such as lying down. In this paper, we propose a simple approach that can detect the fall in a few seconds after it happens and overcomes this problem. This method is based on the Motion Gradient Image and the change of human shape. This solution has been highly accurate in testing and is promising.
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ABSTRACT
Fall is a condition occurring very common in the aged population and increases their risk of unnatural death. If the fall is detected early and alerted, we can timely support. Therefore, many fall detection systems have been developed. However, most of them cannot discriminate against real fall and normal motions of human, such as lying down. In this paper, we propose a simple approach that can detect the fall in a few seconds after it happens and overcomes this problem. This method is based on the Motion Gradient Image and the change of human shape. This solution has been highly accurate in testing and is promising.
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