用RGB-D传感器重建犯罪现场

Abdenour Amamra, Yacine Amara, Khalid Boumaza, Aissa Benayad
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引用次数: 1

摘要

摄影测量是犯罪调查中的一项基本程序,通常使用二维相机进行。虽然有用,但由于缺乏深度信息,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,利用廉价的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场景模拟环境。为了利用三维关键点对捕获的点云进行对齐,提出了一种基于运动的结构方法。然后采用迭代细化和全局优化算法对注册的三维模型进行优化,然后在重建下垫面之前对其进行三角剖分。该模型可用于交互式犯罪侦查和对象动力学仿真。结果表明,对于400万美元× 400万美元的室内场景,我们的解决方案具有视觉上吸引人的渲染效果,仿真准确,定量误差小于18cm。为了说明处理管道1,提供了一个附带的视频。
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Crime Scene Reconstruction with RGB-D Sensors
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 $4m \times 4m$ indoor scene. An accompanying video is provided in order to illustrate the processing pipeline1.
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