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a b s t r a c tWe present a new method to register a pair of images captured in different image modalities. Unlike most of existing systems that register images by aligning single type of visual features, e.g., interest point or contour, we try to align hybrid visual features, including straight lines and interest points. The entire algorithm is carried out in two stages: line-based global transform approximation and point-based local transform adaptation. In the first stage, straight lines derived from edge pixels are employed to find correspondences between two images in order to estimate a global perspective transformation. In the second stage, we divide the entire image into non-overlapping cells with fixed size. The point having the strongest corner response within each cell is selected as the interest point. These points are transformed to other image based on the global transform, and then used to bootstrap a local correspondence search. Experimental evidence shows this method achieves better accuracy for registering visible and long wavelength infrared images/videos as compared to state-of-the-art approaches.

The FIRESENSE FP7 project aims to implement an automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire and extreme weather conditions. This challenging task requires the operation of a multimodal wireless sensor network, the setting up of an infrastructure to publish and access sensor data and the fusion of multiple modalities in a real-time fashion. This paper discusses the multimodal sensor data access and fusion aspects of the project.

Abstract. We present a new method to register a pair of visible (ViS) and infrared (IR) images. Unlike most of existing systems that align interest points of two images, we align lines derived from edge pixels, because the interest points extracted from both images are not always identical, but most major edges detected from one image do appear in another image. To solve feature matching problem, we emphasize the geometric structure alignment of features (lines), instead of descriptorbased individual feature matching. This is due to the fact that image properties and patch statistics of corresponding features might be quite different, especially when one compares ViS image with long wave IR images (thermal information). However, the spatial layout of features for both images always preserves consistency. The last step of our algorithm is to compute the image transform matrix, given minimum 4 pairs of line correspondence. The comparative evaluation for algorithms demonstrates higher accuracy attained by our method when compared to the state-of-the-art approaches. 1