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We present an approach that uses detailed 3D models to detect and classify objects into fine levels of vehicle categories. Unlike other approaches that use silhouette information to fit a 3D model, our approach uses complete appearance from the image. Each 3D model has a set of salient location markers that are determined a-priori. These salient locations represent a sub-sampling of 3D locations that...
This paper presents a joint probabilistic relation graph approach to simultaneously detect and track a large number of vehicles in low frame rate aerial videos. Due to low frame rate, low spatial resolution and sheer number of moving objects, detection and tracking in wide area video poses unique challenges. In this paper, we explore vehicle behavior model from road structure and generate a set of...
In this paper, we propose a novel algorithm for matching optical image to synthetic aperture radar (SAR) image based on scattered edge feature using relaxation Hausdorff distance combined with genetic algorithm. A method is presented to extract scattered edge feature from low signal to noise ratio (SNR) SAR image via statistical and ratio model. Based on the scattered edge image from SAR and optical...
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