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Robust Human Motion Detection via Fuzzy Set Based Image Understanding

机译:通过基于模糊集的图像理解进行可靠的人体运动检测

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This paper presents an image understanding approach to monitor human movement and identify the abnormal circumstance by robust motion detection for the care of the elderly in a home-based environment. In contrast to the conventional approaches which apply either a single feature extraction scheme or a fixed object model for motion detection and tracking, we introduce a multiple feature extraction scheme for robust motion detection. The proposed algorithms include 1) multiple image feature extraction including the fuzzy compactness based detection of interesting points and fuzzy blobs, 2) adaptive image segmentation via multiple features, 3) Hierarchical motion detection, 4) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 5) Fuzzy decision making via multiple features.
机译:本文提出了一种图像理解方法,可通过健壮的运动检测来监视人的运动并识别异常情况,从而在居家环境中照顾老年人。与将单一特征提取方案或固定对象模型应用于运动检测和跟踪的常规方法相比,我们引入了用于鲁棒运动检测的多特征提取方案。所提出的算法包括:1)多个图像特征提取,包括基于模糊紧凑度的兴趣点和模糊斑点检测; 2)通过多个特征进行自适应图像分割; 3)分层运动检测; 4)适应于两种刚性的灵活人体运动模型和非刚性条件; 5)通过多个功能进行模糊决策。

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