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Long-term place recognition for vehicles or robots in outdoor environment is still a tackling issue: numerous changes occur in appearance due to illumination variations or weather phenomena for instance, when using visual sensors. Few methods from the literature try to manage different visual sources while it could favor data interoperability across variable sensors. In this paper, we emphasis our...
A new image specularity removal method is presented in this paper. This method is based on the polarization imaging through global energy minimization. Traditional color-based methods generate severe color distortions, and local-patch-based algorithms produce limited results without integrating the long range information. To handle these limitations, the proposed method uses polarization images to...
Stereo matching is a basic yet important issue in the research of computer vision. A key problem of stereo matching is how to efficiently use the information provided by the neighborhood. In some existing disparity refinement methods, it is observed that the disparity is fused only after having the disparity map, which unfortunately causes the lost of cost information. To make a better disparity fusion,...
A fast and efficient color stereo matching algorithm is presented in this paper. The intended application is in the field of intelligent vehicles. The algorithm is initialized with selecting an appropriate color space giving the smallest disparity error. Dynamic cross-based aggregation region is then applied. To be fast and also robust to noise and illumination variation, the algorithm explores sparse...
Pedestrian detection is an important but challenging component of an Intelligent Transportation System. In this paper, we describe a pedestrian detection system based on a monocular vision with a Far-Infrared camera (FIR). We propose an original feature representation, called Intensity Self Similarity (ISS), adapted to pedestrian detection in FIR images. The ISS representation is based on the relative...
In the framework of Stokes parameters imaging, polarization-encoded images have four channels. The potential of such multidimensional structure comes from the set of physical information they carry about the local nature of the target. However, the noise that affects the intensity measurement may induce the non physical meaning of Stokes parameters making awkward their analysis and interpretation...
In the framework of Stokes parameters imaging, polarization-encoded images have four channels which make physical interpretation of such multidimensional structures hard to grasp at once. Furthermore, the information content is intricately combined in the parameters channels which involve the need for a proper tool that allows the analysis and understanding of polarization-encoded images. In this...
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