论文标题
在线Panoptic 3D重建作为线性分配问题
Online panoptic 3D reconstruction as a Linear Assignment Problem
论文作者
论文摘要
实时整体场景理解将使机器能够以比目前可能更详细的方式来解释其周围环境。虽然全景图像分割方法使图像分割更接近此目标，但必须将这些信息相对于3D环境描述，以使计算机能够有效地利用它。在本文中，我们研究了从3D中的全景图像分割中依次重建静态环境的方法。我们专门针对实时操作：该算法必须严格在线处理数据，并能够以相对快速的帧速率运行。此外，该方法应适用于足够大的实际应用环境。通过应用简单但功能强大的数据合作算法，我们纯粹在线操作时，我们的表现要优于早期的类似作品。我们的方法还能够达到足够高的帧速率以实时应用，并且也可扩展到较大的环境。源代码和进一步的演示将向公众发布：\ url {https://tutvision.github.io/online-panoptic-3d/}
Real-time holistic scene understanding would allow machines to interpret their surrounding in a much more detailed manner than is currently possible. While panoptic image segmentation methods have brought image segmentation closer to this goal, this information has to be described relative to the 3D environment for the machine to be able to utilise it effectively. In this paper, we investigate methods for sequentially reconstructing static environments from panoptic image segmentations in 3D. We specifically target real-time operation: the algorithm must process data strictly online and be able to run at relatively fast frame rates. Additionally, the method should be scalable for environments large enough for practical applications. By applying a simple but powerful data-association algorithm, we outperform earlier similar works when operating purely online. Our method is also capable of reaching frame-rates high enough for real-time applications and is scalable to larger environments as well. Source code and further demonstrations are released to the public at: \url{https://tutvision.github.io/Online-Panoptic-3D/}
