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首页> 外文期刊>電気学会論文誌 C:電子·情報·システム部門誌 >Panoramic 3D Reconstruction by Fusing Color Intensity and Laser Range Data
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Panoramic 3D Reconstruction by Fusing Color Intensity and Laser Range Data

机译:通过融合颜色强度和激光距离数据进行全景3D重建

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Technology for capturing panoramic (360 degrees) three-dimensional information in a real environment have many applications in fields: virtual and complex reality, security, robot navigation, and so forth. In this study, we examine an acquisition device constructed of a regular CCD camera and a 2D laser range scanner, along with a technique for panoramic 3D reconstruction using a data fusion algorithm based on an energy minimization framework. The acquisition device can capture two types of data of a panoramic scene without occlusion between two sensors: a dense spatio-temporal volume from a camera and distance information from a laser scanner. We resample the dense spatio-temporal volume for generating a dense multi-perspective panorama that has equal spatial resolution to that of the original images acquired using a regular camera, and also estimate a dense panoramic depth-map corresponding to the generated reference panorama by extracting trajectories from the dense spatio-temporal volume with a selecting camera. Moreover, for determining distance information robustly, we propose a data fusion algorithm that is embedded into an energy minimization framework that incorporates active depth measurements using a 2D laser range scanner and passive geometry reconstruction from an image sequence obtained using the CCD camera. Thereby, measurement precision and robustness can be improved beyond those available by conventional methods using either passive geometry reconstruction (stereo vision) or a laser range scanner. Experimental results using both synthetic and actual images show that our approach can produce high-quality panoramas and perform accurate 3D reconstruction in a panoramic environment.
机译:在真实环境中捕获全景(360度)三维信息的技术在以下领域有许多应用:虚拟和复杂的现实,安全性,机器人导航等。在这项研究中,我们研究了由常规CCD相机和2D激光测距仪构成的采集设备,以及使用基于能量最小化框架的数据融合算法进行全景3D重建的技术。采集设备可以捕获两种类型的全景场景数据,而不会在两个传感器之间发生闭塞:来自相机的密集时空体积和来自激光扫描仪的距离信息。我们重新采样密集的时空体积,以生成具有与使用常规相机获取的原始图像相同的空间分辨率的密集的多视角全景图,并通过提取来估计与生成的参考全景图相对应的密集全景深度图选择相机从密集的时空体积中绘制轨迹。此外,为稳健地确定距离信息,我们提出了一种数据融合算法,该算法嵌入到能量最小化框架中,该框架融合了使用2D激光测距仪进行的主动深度测量以及根据使用CCD相机获得的图像序列进行的被动几何重构。从而,可以提高测量精度和鲁棒性,使其超过使用无源几何重构(立体视觉)或激光范围扫描仪的常规方法所能提供的精度。使用合成图像和实际图像进行的实验结果表明,我们的方法可以生成高质量的全景图,并在全景环境中执行准确的3D重建。

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