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A morphological approach to detect human in video

机译:一种探测人类视频的形态学方法

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摘要

Human detection in video is a challenging task due to complex backgrounds, occlusions, variations in lighting conditions and so on. The main objective of this paper is to determine the presence of human in a video scene. It finds usage in determining number of persons which is found to be a useful metric in understanding the interested participants and their interaction with the environment. The foreground is detected using Gaussian mixture model and is processed to remove unwanted noise by applying suitable morphological operations forming a binary image. The dominant blob region is identified using connected component labeling technique and averaging methods are employed between clean foreground mask and binary image. Finally, edge detection is applied to each processed frame and edge details in the segmented blob displays the presence of the human in the scene. The qualitative results of the proposed system show improved detection accuracy avoiding missed and false detections.
机译:由于复杂的背景,闭塞,照明条件的变化等,人类检测是一个具有挑战性的任务。本文的主要目标是确定人类在视频场景中的存在。它发现了确定在确定感兴趣的参与者及其与环境互动方面是一个有用的公制的人数的用法。使用高斯混合模型检测前景,并通过应用形成二进制图像的合适的形态学操作来处理以消除不需要的噪声。使用连接的组件标记技术识别优势BLOB区域,并且在清洁前景掩模和二进制图像之间采用平均方法。最后,将边缘检测应用于分段百波形中的每个处理的帧和边缘细节显示在场景中的存在。所提出的系统的定性结果显示出改善的检测精度避免错过和虚假检测。

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