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Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices

机译:移动设备上深度图像的超高帧速体积积分

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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.
机译:体积方法提供了将多个深度图像集成到完整3D模型中的有效,灵活和简单的方法。它们提供了密集且逼真的3D重建,并且GPU上的并行实现在现代图形硬件上实现了实时性能。然而,为了在移动设备上运行这样的方法,向用户提供移动自由和瞬时重建反馈仍然是挑战。在本文中,我们对基于体素块哈希的现有体积积分方法进行了一系列修改,从而显着提高了它们的性能并使它们适用于平板电脑应用。我们提出(i)基本数据结构及其分配和集成的优化; (ii)高度优化的射线广播管道; (iii)摄像机跟踪器的扩展,以合并IMU数据。因此,总体而言,我们的系统在Nvidia Shield Tablet上的帧频高达47 Hz,在Nvidia GTX Titan XGPU上的帧频高达910 Hz,甚至在不可视的情况下甚至超过1.1 kHz。

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