Detecting partial occlusion of humans using snakes and neural networks

Detecting partial occlusion of humans using snakes and neural networks
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使用蛇和神经网络检测人体的部分遮挡

DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
R. Adams
R. Adams
中科院分区：
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文献类型：
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作者：
K. Tabb;N. Davey;S. George;R. Adams

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摘要：本文总结了旨在检测​​图像或一系列图像中移动人体的计算机系统的发展。该系统结合使用主动轮廓模型“蛇”（可检测图像中的人体物体）和 2 层前馈反向传播神经网络，将检测到的形状分类为人类或非人类。研究发现，将神经网络的输出值与其置信值相结合提供了一种将看不见的形状分类为“人类”和“非人类”的方法。此外，置信值可以提供对检测到的人体的遮挡程度的测量。
Abstract: This paper summarises the development of a computer system designed to detect moving humans in an image or series of images. The system combines the use of active contour models, ‘snakes’, which detect human objects in an image, with a 2 layer feedforward backpropagation neural network, to categorise the detected shape as human, or not. It was found that combining the neural network’s output values with its confidence value provided a means of classifying unseen shapes into ‘human’ and ‘non-human’. Moreover the confidence value can provide a measure of the degree of occlusion of a detected human.