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Evaluation of image processing algorithms on vehicle safety system based on free-viewpoint image rendering

机译:基于自由视点图像渲染的车辆安全系统图像处理算法评估

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Development of algorithms for vehicle safety systems, which support safety driving, takes a long period of time and a huge cost because it requires an evaluation stage where huge combinations of possible driving situations should be evaluated by using videos which are captured beforehand in real environments. In this paper, we address this problem by using free viewpoint images instead of the real images. More concretely, we generate free-viewpoint images from a combination of a 3D point cloud measured by laser scanners and an omni-directional image sequence acquired in a real environment. We basically rely on the 3D point cloud for geometrically correct virtual viewpoint images. In order to remove the holes caused by the unmeasured region of the 3D point cloud and to remove false silhouettes in surface reconstruction, we have developed a technique of free-viewpoint image generation that uses both a 3D point cloud and depth information extracted from images. In the experiments, we have evaluated our framework with a white line detection algorithm and experimental results have shown the applicability of free-viewpoint images for evaluation of algorithms.
机译:支持安全驾驶的车辆安全系统算法的开发需要很长一段时间和巨大的成本,因为它需要通过使用预先在真实环境中捕获的视频来评估可能的驾驶情况的巨大组合的评估阶段。在本文中,我们通过使用免费视点图像而不是真实图像来解决这个问题。更具体地,我们从激光扫描仪测量的3D点云的组合和在真实环境中获取的全方位图像序列的组合生成义视点图像。我们基本上依赖于3D点云进行几何正确校正虚拟视点图像。为了去除由3D点云的未测量区域引起的孔并在表面重建中删除虚假剪影,我们开发了一种使用从图像中提取的3D点云和深度信息的自由视图像生成技术。在实验中,我们已经评估了使用白线检测算法的框架,并且实验结果表明了自由观点图像的适用性进行评估算法。

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