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Templateless Non-rigid Reconstruction and Motion Tracking with a Single RGB-D Camera
Accepted to IEEE Transactions on Image Processing 2017.

Kangkan Wang, Guofeng Zhang, Shihong Xia

Abstract
We present a novel templateless approach for nonrigid reconstruction and motion tracking using a single RGB-D camera. Without any template prior, our system achieves accurate reconstruction and tracking for considerably deformable objects. To robustly register the input sequence of partial depth scans with dynamic motion, we propose an efficient local-toglobal hierarchical optimization framework inspired by the idea of traditional structure-from-motion. Our proposed framework mainly consists of two stages, local nonrigid bundle adjustment and global optimization. To eliminate error accumulation during nonrigid registration of loop motion sequences, we split the full sequence into several segments and apply local nonrigid bundle adjustment to align each segment locally. Global optimization is then adopted to combine all segments and handle the drift problem through loop-closure constraint. By fitting to the input partial data, a deforming 3D model sequence of dynamic objects is finally generated. Experiments on both synthetic and real test datasets and comparisons with state-of-the-arts demonstrate that our approach can handle considerable motions robustly and efficiently, and reconstruct high-quality 3D model sequences without drift.
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Templateless Non-rigid Reconstruction and Motion Tracking with a Single RGB-D Camera.  Accepted to IEEE Transactions on Image Processing 2017. [PDF 6,815KB] [Video 11,539KB]