Kähler Olaf, Adrian Prisacariu Victor, Yuheng Ren Carl, Sun Xin, Torr Philip, Murray David
IEEE Trans Vis Comput Graph. 2015 Nov;21(11):1241-50. doi: 10.1109/TVCG.2015.2459891.
Volumetric methods provide efficient, flexible and simple ways of integrating multiple depth images into a full 3D model. They provide dense and photorealistic 3D reconstructions, and parallelised implementations on GPUs achieve real-time performance on modern graphics hardware. To run such methods on mobile devices, providing users with freedom of movement and instantaneous reconstruction feedback, remains challenging however. In this paper we present a range of modifications to existing volumetric integration methods based on voxel block hashing, considerably improving their performance and making them applicable to tablet computer applications. We present (i) optimisations for the basic data structure, and its allocation and integration; (ii) a highly optimised raycasting pipeline; and (iii) extensions to the camera tracker to incorporate IMU data. In total, our system thus achieves frame rates up 47 Hz on a Nvidia Shield Tablet and 910 Hz on a Nvidia GTX Titan XGPU, or even beyond 1.1 kHz without visualisation.
容积法提供了将多个深度图像集成到完整3D模型中的高效、灵活且简单的方法。它们能提供密集且逼真的3D重建，并且在GPU上的并行实现可在现代图形硬件上实现实时性能。然而，要在移动设备上运行此类方法，为用户提供移动自由度和即时重建反馈，仍然具有挑战性。在本文中，我们对基于体素块哈希的现有容积积分方法进行了一系列修改，显著提高了它们的性能，并使其适用于平板电脑应用。我们提出了：（i）对基本数据结构及其分配和积分的优化；（ii）高度优化的光线投射管道；以及（iii）相机跟踪器的扩展，以纳入IMU数据。总的来说，我们的系统在英伟达护盾平板电脑上实现了高达47Hz的帧率，在英伟达GTX泰坦X GPU上实现了910Hz的帧率，甚至在不进行可视化的情况下超过了1.1kHz。
