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Crime Scene Reconstruction with RGB-D Sensors

机译:RGB-D传感器犯罪现场重建

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摘要

Photographic surveying, a fundamental procedure in crime investigation, is typically performed using 2D cameras. Although useful, such cameras remain limited due to the lack of depth information. In this work, we propose a 3D reconstruction solution that leverages the advantages of cheap RGB-D sensors to create a 3D model of the crime scene and to provide the investigator with an interactive crime scenario simulation environment. A structure from motion approach is proposed in order to align the captured point clouds on each other using 3D key points. An iterative refinement and a global optimization algorithm are later adapted for the optimization of the registered 3D model, which is then triangulated before the underlying surface is reconstructed. The resulting model is used for interactive crime investigation and object dynamics simulation. The obtained results show the elrectiveness of our solution with a visually appealing rendering, an accurate simulation and a quantitative error of less than 18cm for the $4m imes 4m$ indoor scene. An accompanying video is provided in order to illustrate the processing pipeline1.
机译:摄影测量是犯罪调查中的基本程序,通常使用2D摄像机进行。虽然有用,但由于缺乏深度信息,这种相机仍然有限。在这项工作中,我们提出了一个3D重建解决方案,利用便宜的RGB-D传感器的优势来创建犯罪现场的3D模型,并为调查员提供交互式犯罪方案模拟环境。提出了一种来自运动方法的结构,以便使用3D密钥点对准捕获的点云。稍后适于迭代细化和全局优化算法,用于优化登记的3D模型,然后在重建底层表面之前三角化。结果模型用于交互式犯罪调查和对象动力学模拟。所获得的结果表明,我们的解决方案具有视觉上吸引人的渲染,精确的模拟和4m次为4M $ 400美元的400万美元的定量误差。提供了伴随的视频,以说明处理管道 1

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