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Crime Scene Reconstruction with RGB-D Sensors

机译:使用RGB-D传感器的犯罪现场重建

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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:摄影调查是犯罪调查中的基本程序,通常使用2D相机进行。尽管有用,但是由于缺乏深度信息,这种相机仍然受到限制。在这项工作中,我们提出了一种3D重建解决方案,该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,并为调查人员提供交互式犯罪场景模拟环境。提出了一种来自运动方法的结构,以便使用3D关键点将捕获的点云彼此对齐。迭代优化和全局优化算法随后适用于注册3D模型的优化,然后在构造底层表面之前将其三角剖分。生成的模型用于交互式犯罪调查和对象动力学模拟。获得的结果显示了我们的解决方案的正确性,具有视觉吸引力的渲染效果,准确的模拟效果,并且对于400万美元乘以4m美元的室内场景,其定量误差小于18cm。提供随附的视频,以说明处理流程 1

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