Robust Person Detection using Far Infrared Camera for Image Fusion

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.