Scene flow based stereo augmentation reconstruction

In this paper, an effective technique is presented to reconstruct an accurate and reliable 3D surface model from multi-view stereo. Different from classical means, we investigate to integrate stereo and motion analysis approach in which optical flow-scene flow framework is involved. In this scheme, reconstruction is decoupled into two stages. Firstly, depth of feature points is recovered and in turn is used for building an intermediate polygonal mesh; Secondly, projection feedback on comparison views, which is generated on assumption of the established coarse mesh model, is carefully introduced to deform the primitive mesh model so as to improve its quality dramatically. The discrepancy of observation on comparison views and the corresponding predictive feedback is quantitatively evaluated by optical flow field and is employed to derive the corresponding scene flow vector field subsequently, which is then used for surface deformation. As optical flow vector field estimation outperforms traditional dense disparity for its inherent advantage of being robust to illumination change and being optimized and smoothed in global sense, the deformed surface can be improved in accuracy, which is firmly validated by encouraging experimental results.