Mathieu Salzmann received his B.Sc and M.Sc degrees in computer science in 2004 from EPFL (Swiss Federal Institute of Technology). He obtained his PhD degree in computer vision in 2009 from EPFL. He then joined the International Computer Science Institute and the EECS department at UC Berkeley as a postdoctoral fellow. Recently, he joined TTI Chicago as a Research Assistant Professor. His research interests include non-rigid shape recovery, human pose estimation, and optimization techniques for computer vision.

• Introduction.- Early Approaches to Non-Rigid Reconstruction.- Formalizing Template-Based Reconstruction.- Performing Template-Based Reconstruction.- Formalizing Non-Rigid Structure from Motion.- Performing Non-Rigid Structure from Motion.- Future Directions.

Mathieu Salzmann received his B.Sc and M.Sc degrees in computer science in 2004 from EPFL (Swiss Federal Institute of Technology). He obtained his PhD degree in computer vision in 2009 from EPFL. He then joined the International Computer Science Institute and the EECS department at UC Berkeley as a postdoctoral fellow. Recently, he joined TTI Chicago as a Research Assistant Professor. His research interests include non-rigid shape recovery, human pose estimation, and optimization techniques for computer vision.

• Introduction.- Early Approaches to Non-Rigid Reconstruction.- Formalizing Template-Based Reconstruction.- Performing Template-Based Reconstruction.- Formalizing Non-Rigid Structure from Motion.- Performing Non-Rigid Structure from Motion.- Future Directions.

Mathieu Salzmann received his B.Sc and M.Sc degrees in computer science in 2004 from EPFL (Swiss Federal Institute of Technology). He obtained his PhD degree in computer vision in 2009 from EPFL. He then joined the International Computer Science Institute and the EECS department at UC Berkeley as a postdoctoral fellow. Recently, he joined TTI Chicago as a Research Assistant Professor. His research interests include non-rigid shape recovery, human pose estimation, and optimization techniques for computer vision.

• Introduction.- Early Approaches to Non-Rigid Reconstruction.- Formalizing Template-Based Reconstruction.- Performing Template-Based Reconstruction.- Formalizing Non-Rigid Structure from Motion.- Performing Non-Rigid Structure from Motion.- Future Directions.