Authors
Kaiwen Guo, Jonathan Taylor, Sean Fanello, Andrea Tagliasacchi, Mingsong Dou, Philip Davidson, Adarsh Kowdle, Shahram Izadi
Publication date
2018/9/5
Conference
2018 International Conference on 3D Vision (3DV)
Pages
596-605
Publisher
IEEE
Description
Real time non-rigid reconstruction pipelines are extremely computationally expensive and easily saturate the highest end GPUs currently available. This requires careful strategic choices to be made about a set of highly interconnected parameters that divide up the limited compute. At the same time, offline systems, prove the value of increasing voxel resolution, more iterations, and higher frame rates. To this end, we demonstrate a set of remarkably simple but effective modifications to these algorithms that significantly reduce the average per-frame computation cost allowing these parameters to be increased. Specifically, we divide the depth stream into sub-frames and fusion-frames, disabling both model accumulation (fusion) and non-rigid alignment (model tracking) on the former. Instead, we efficiently track point correspondences across neighboring sub-frames. We then leverage these correspondences to …
Total citations
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Scholar articles
K Guo, J Taylor, S Fanello, A Tagliasacchi, M Dou… - 2018 International Conference on 3D Vision (3DV), 2018