Capturing Relightable Human Performances under General Uncontrolled Illumination

We present a novel approach to create relightable free‐viewpoint human performances from multi‐view video recorded under general uncontrolled and uncalibated illumination. We first capture a multi‐view sequence of an actor wearing arbitrary apparel and reconstruct a spatio‐temporal coherent coarse 3D model of the performance using a marker‐less tracking approach. Using these coarse reconstructions, we estimate the low‐frequency component of the illumination in a spherical harmonics (SH) basis as well as the diffuse reflectance, and then utilize them to estimate the dynamic geometry detail of human actors based on shading cues. Given the high‐quality time‐varying geometry, the estimated illumination is extended to the all‐frequency domain by re‐estimating it in the wavelet basis. Finally, the high‐quality all‐frequency illumination is utilized to reconstruct the spatially‐varying BRDF of the surface. The recovered time‐varying surface geometry and spatially‐varying non‐Lambertian reflectance allow us to generate high‐quality model‐based free view‐point videos of the actor under novel illumination conditions. Our method enables plausible reconstruction of relightable dynamic scene models without a complex controlled lighting apparatus, and opens up a path towards relightable performance capture in less constrained environments and using less complex acquisition setups.

[1]  Wojciech Matusik,et al.  A data-driven reflectance model , 2003, ACM Trans. Graph..

[2]  Paul E. Debevec,et al.  A median cut algorithm for light probe sampling , 2005, SIGGRAPH Courses.

[3]  Hans-Peter Seidel,et al.  Image-based reconstruction of spatial appearance and geometric detail , 2003, TOGS.

[4]  Hans-Peter Seidel,et al.  Relighting objects from image collections , 2009, CVPR 2009.

[5]  Jitendra Malik,et al.  Recovering photometric properties of architectural scenes from photographs , 1998, SIGGRAPH.

[6]  André Gagalowicz,et al.  Image-based rendering of diffuse, specular and glossy surfaces from a single image , 2001, SIGGRAPH.

[7]  Athinodoros S. Georghiades,et al.  Recovering 3-D Shape and Reflectance From a Small Number of Photographs , 2003, Rendering Techniques.

[8]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[9]  P. Hanrahan,et al.  Triple product wavelet integrals for all-frequency relighting , 2004, SIGGRAPH 2004.

[10]  Pat Hanrahan,et al.  An efficient representation for irradiance environment maps , 2001, SIGGRAPH.

[11]  Markus H. Gross,et al.  Scalable 3D video of dynamic scenes , 2005, The Visual Computer.

[12]  Paul Debevec,et al.  Inverse global illumination: Recovering re?ectance models of real scenes from photographs , 1998 .

[13]  Hans-Peter Seidel,et al.  Motion capture using joint skeleton tracking and surface estimation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Hans-Peter Seidel,et al.  Performance capture from sparse multi-view video , 2008, SIGGRAPH 2008.

[15]  Ramesh Raskar,et al.  Image-based visual hulls , 2000, SIGGRAPH.

[16]  Derek Bradley,et al.  Markerless garment capture , 2008, SIGGRAPH 2008.

[17]  Steven M. Seitz,et al.  Shape and Spatially-Varying BRDFs from Photometric Stereo , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  James T. Kajiya,et al.  The rendering equation , 1986, SIGGRAPH.

[19]  Yasuyuki Matsushita,et al.  High-quality shape from multi-view stereo and shading under general illumination , 2011, CVPR 2011.

[20]  Hans-Peter Seidel,et al.  Seeing People in Different Light — Joint Shape , Motion , and Reflectance Capture , 2007 .

[21]  Katsushi Ikeuchi,et al.  Object shape and reflectance modeling from observation , 1997, SIGGRAPH.

[22]  Ronen Basri,et al.  Photometric stereo with general, unknown lighting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[23]  Hans-Peter Seidel,et al.  Performance capture from sparse multi-view video , 2008, ACM Trans. Graph..

[24]  Andrew Jones,et al.  Relighting human locomotion with flowed reflectance fields , 2006, EGSR '06.

[25]  Paul A. Beardsley,et al.  Image-based 3D photography using opacity hulls , 2002, ACM Trans. Graph..

[26]  Peter F. Sturm,et al.  Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions , 2009, International Journal of Computer Vision.

[27]  Adrian Hilton,et al.  Surface Capture for Performance-Based Animation , 2007, IEEE Computer Graphics and Applications.

[28]  Hans-Peter Seidel,et al.  Shading-based dynamic shape refinement from multi-view video under general illumination , 2011, 2011 International Conference on Computer Vision.

[29]  Andrew Gardner,et al.  Performance relighting and reflectance transformation with time-multiplexed illumination , 2005, ACM Trans. Graph..

[30]  Pat Hanrahan,et al.  A signal-processing framework for inverse rendering , 2001, SIGGRAPH.

[31]  Jovan Popović,et al.  Dynamic shape capture using multi-view photometric stereo , 2009, SIGGRAPH 2009.

[32]  Slobodan Ilic,et al.  Free-form mesh tracking: A patch-based approach , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[33]  Paul E. Debevec,et al.  Acquiring the reflectance field of a human face , 2000, SIGGRAPH.

[34]  Kiriakos N. Kutulakos,et al.  Multi-view scene capture by surfel sampling: from video streams to non-rigid 3D motion, shape and reflectance , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[35]  Richard Szeliski,et al.  A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  Wojciech Matusik,et al.  Articulated mesh animation from multi-view silhouettes , 2008, ACM Trans. Graph..

[37]  Chengbo Li An efficient algorithm for total variation regularization with applications to the single pixel camera and compressive sensing , 2010 .

[38]  A. Aydin Alatan,et al.  Efficient graph-based image segmentation via speeded-up turbo pixels , 2010, 2010 IEEE International Conference on Image Processing.

[39]  Sebastian Thrun,et al.  Video-based reconstruction of animatable human characters , 2010, ACM Trans. Graph..

[40]  Björn Stenger,et al.  Non-rigid Photometric Stereo with Colored Lights , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[41]  Christian Theobalt,et al.  Full Body Performance Capture under Uncontrolled and Varying Illumination: A Shading-Based Approach , 2012, ECCV.