%0 Conference Paper %1 conf/vrst/WenningerABLB20 %A Wenninger, Stephan %A Achenbach, Jascha %A Bartl, Andrea %A Latoschik, Marc Erich %A Botsch, Mario %B VRST %D 2020 %E Teather, Robert J. %E Joslin, Chris %E Stuerzlinger, Wolfgang %E Figueroa, Pablo %E Hu, Yaoping %E Batmaz, Anil Ufuk %E Lee, Wonsook %E Ortega, Francisco %I ACM %K myown %P 29:1-29:11 %T Realistic Virtual Humans from Smartphone Videos. %U https://dl.acm.org/doi/pdf/10.1145/3385956.3418940 %X This paper introduces an automated 3D-reconstruction method for generating high-quality virtual humans from monocular smartphone cameras. The input of our approach are two video clips, one capturing the whole body and the other providing detailed close-ups of head and face. Optical flow analysis and sharpness estimation select individual frames, from which two dense point clouds for the body and head are computed using multi-view reconstruction. Automatically detected landmarks guide the fitting of a virtual human body template to these point clouds, thereby reconstructing the geometry. A graph-cut stitching approach reconstructs a detailed texture. Our results are compared to existing low-cost monocular approaches as well as to expensive multi-camera scan rigs. We achieve visually convincing reconstructions that are almost on par with complex camera rigs while surpassing similar low-cost approaches. The generated high-quality avatars are ready to be processed, animated, and rendered by standard XR simulation and game engines such as Unreal or Unity %@ 978-1-4503-7619-8

@inproceedings{conf/vrst/WenningerABLB20, abstract = {This paper introduces an automated 3D-reconstruction method for generating high-quality virtual humans from monocular smartphone cameras. The input of our approach are two video clips, one capturing the whole body and the other providing detailed close-ups of head and face. Optical flow analysis and sharpness estimation select individual frames, from which two dense point clouds for the body and head are computed using multi-view reconstruction. Automatically detected landmarks guide the fitting of a virtual human body template to these point clouds, thereby reconstructing the geometry. A graph-cut stitching approach reconstructs a detailed texture. Our results are compared to existing low-cost monocular approaches as well as to expensive multi-camera scan rigs. We achieve visually convincing reconstructions that are almost on par with complex camera rigs while surpassing similar low-cost approaches. The generated high-quality avatars are ready to be processed, animated, and rendered by standard XR simulation and game engines such as Unreal or Unity}, added-at = {2022-09-08T10:57:22.000+0200}, author = {Wenninger, Stephan and Achenbach, Jascha and Bartl, Andrea and Latoschik, Marc Erich and Botsch, Mario}, biburl = {https://www.bibsonomy.org/bibtex/284ed6d2c6762d11e29e4de114f5032c7/abartl}, booktitle = {VRST}, crossref = {conf/vrst/2020}, editor = {Teather, Robert J. and Joslin, Chris and Stuerzlinger, Wolfgang and Figueroa, Pablo and Hu, Yaoping and Batmaz, Anil Ufuk and Lee, Wonsook and Ortega, Francisco}, ee = {https://doi.org/10.1145/3385956.3418940}, interhash = {f08bfebf60917fcc94f4f836171b0b53}, intrahash = {84ed6d2c6762d11e29e4de114f5032c7}, isbn = {978-1-4503-7619-8}, keywords = {myown}, note = {Best paper award 🏆}, pages = {29:1-29:11}, publisher = {ACM}, timestamp = {2022-09-08T10:57:22.000+0200}, title = {Realistic Virtual Humans from Smartphone Videos.}, url = {https://dl.acm.org/doi/pdf/10.1145/3385956.3418940}, year = 2020 }