Robust Person Detection using Far Infrared Camera for Image Fusion
Robust Person Detection using Far Infrared Camera for Image Fusion
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DOI：
10.1109/icicic.2007.501
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发表时间：
2007-09
期刊：
影响因子：
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通讯作者：
Thi Thi Zin-Thi;H. Takahashi;H. Hama
中科院分区：
文献类型：
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作者：
Thi Thi Zin-Thi;H. Takahashi;H. Hama
在本文中，我们提出了一个强大的方法，使用远红外图像的人检测。为了提取初始指定的头部区域，阈值和形态学操作应用使用强度信息。在这些区域中，一些错误提取的区域被删除使用的模式的人的头部基于Sobel边缘图像的局部最大值。在分割出头部区域后，利用该比值对人体和腿部区域进行粗略估计。利用这些估计区域的Sobel边缘直方图来确定分割后的头部。该方法可适用于室内和室外场景中的近距离和远距离的人检测。此外，我们提出了另一种新的算法使用的重心的移动模式。这是一种非常简单的方法，尤其适用于近距离的图像。我们的实验证明了所提出的方法的有效性和处理夜视应用中的人检测的优势。最后讨论了可见光与远红外相机的图像融合问题。
In this paper we present a robust method for person detection using far infrared images. To extract initial nominated head regions, thresholding and morphological operations are applied using intensity information. Among these regions, some of wrongly extracted regions are removed using the pattern of person head based on the local maximums of Sobel edge image. After the head regions are segmented, the person body and legs region are roughly estimated by the ratios. The histograms of Sobel edge of such estimated regions are used to confirm the segmented head. This method can be applicable to person detection at both near and far distances in indoor and outdoor scenes. Moreover, we propose another novel algorithm using the movement pattern of gravity centers. It is a very simple way, especially valid for images at near distances. Our experiments demonstrate the effectiveness of the proposed method and the advantages in dealing with person detection for night vision applications. Finally, image fusion of visible and far infrared cameras is discussed.