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Background Subtraction and Human Detection in Outdoor Videos using Fuzzy Logic

机译:使用模糊逻辑的户外视频中的背景减法和人类检测

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This paper presents a scale and view invariant approach for human detection in the presence of various other objects like animals, vehicles, etc. Human detection is one of the essential steps in applications like activity recognition, gait recognition, human centric surveillance etc. Inaccurate detection of humans in such applications may increase the number of false alarms. In the proposed work, fuzzy logic has been used to model a robust background for object detection. Three different features are extracted from the contours of the detected objects. These features are aggregated using fuzzy inference system. Then human contour is identified using template matching. The proposed method consists of four main steps; Moving Object Detection, Feature Extraction, Feature Aggregation, and Human Contour Detection.
机译:本文提出了在存在动物,车辆等各种其他物体的存在下人类检测的规模和观点的不变方法,如动物,车辆等人类检测是活动识别,步态识别,人类中心监测等的应用中的基本步骤之一。不准确的检测在这种应用中的人类可能会增加误报的数量。在所提出的工作中,模糊逻辑已被用于模拟对象检测的强大背景。从检测到的对象的轮廓中提取三种不同的特征。这些功能使用模糊推理系统聚合。然后使用模板匹配识别人轮廓。该方法由四个主要步骤组成;移动物体检测,特征提取,特征聚合和人体轮廓检测。

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