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首页> 外文会议>2017 15th International Conference on Quality in Research : International Symposium on Electrical and Computer Engineering >Headgear recognition by decomposing human images in the thermal infrared spectrum
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Headgear recognition by decomposing human images in the thermal infrared spectrum

机译：通过分解热红外光谱中的人像来识别头盔

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摘要

Surveillance systems play a critical role in security and surveillance. A surveillance system with cameras that work in the visible spectrum is sufficient for most cases. However, problems may arise during the night, or in areas with less than ideal illumination conditions. Cameras with thermal infrared technology can be a better option in these situations since they do not rely on illumination to observe the environment. Furthermore, in our daily lives, it is common for humans to wear headgears such as glasses, masks, and hats. In surveillance, such headgears can be a hindrance to the identification of a person, and hence pose a certain degree of risk. This is not ideal in areas where the identity of a person is important, for example, in a bank. Therefore, in this paper we propose a headgear recognition method using an innovative decomposition approach on thermal infrared images. The decomposition method is based on Robust Principal Component Analysis, a modification of the popular Principal Component Analysis. The proposed method performs decomposition on a human image and isolates headgears in the image for recognition purposes. Experiments were conducted to evaluate the capability of the proposed method. The results show a positive outcome when compared with other methods.
机译：监视系统在安全和监视中起着至关重要的作用。在大多数情况下，带有在可见光谱范围内工作的摄像机的监视系统就足够了。但是，在夜间或照明条件不理想的区域可能会出现问题。在这些情况下，采用热红外技术的相机可能是更好的选择，因为它们不依靠照明来观察环境。此外，在我们的日常生活中，人类通常戴着诸如眼镜，口罩和帽子之类的头饰。在监视中，此类头饰可能会妨碍身份识别，因此会带来一定程度的风险。在人们的身份很重要的区域，例如在银行中，这是不理想的。因此，在本文中，我们提出了一种使用新颖的分解方法对热红外图像进行头饰识别的方法。分解方法基于稳健的主成分分析，该方法是对流行的主成分分析的改进。所提出的方法对人的图像进行分解，并分离出图像中的头饰以进行识别。实验进行了评估该方法的能力。与其他方法相比，结果显示出积极的结果。

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