Multi-volume mapping and tracking for real-time RGB-D sensing

In recent years, many research has been devoted to real-time dense mapping and tracking techniques due to the availability of low-cost RGB-D cameras. In this paper, we present a novel multi-volume mapping and tracking algorithm to generate photo-realistic mapping while maintaining accurate and robust camera tracking. The algorithm deploys one small volume of high voxel resolution to obtain detailed maps of near-field objects, while utilizes another big volume of low voxel resolution to increase robustness of tracking by including far-field scenes. The experimental results show that our multivolume processing scheme achieves an objective quality gain of 2 dB in PSNR and 0.2 in SSIM. Our approach is capable of real-time sensing with approximately 30 fps and can be implemented on a modern GPU.</p

Multi-volume mapping and tracking for real-time RGB-D sensing

In recent years, many research has been devoted to real-time dense mapping and tracking techniques due to the availability of low-cost RGB-D cameras. In this paper, we present a novel multi-volume mapping and tracking algorithm to generate photo-realistic mapping while maintaining accurate and robust camera tracking. The algorithm deploys one small volume of high voxel resolution to obtain detailed maps of near-field objects, while utilizes another big volume of low voxel resolution to increase robustness of tracking by including far-field scenes. The experimental results show that our multivolume processing scheme achieves an objective quality gain of 2 dB in PSNR and 0.2 in SSIM. Our approach is capable of real-time sensing with approximately 30 fps and can be implemented on a modern GPU