Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
M.A. Eric Thil
Nicole Stephanie Buhlinger
Keonna Cunningham
Dr. Oliver Wasenmüller
Dr. Gabriele Bleser
Dr. Bertram Taetz
M.Sc Rashed Al Koutayni
Yuriy Anisimov
Ramy Battrawy
Hammad Butt
Mahdi Chamseddine
Steve Dias da Cruz
M.Sc. Fangwen Shu
Torben Fetzer
Michael Fürst
Christiano Couto Gava
Vladislav Golyanik
Hartmut Feld
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Nareg Minaskan Karabid
Mathias Musahl
Peter Neigel
Manthan Pancholi
Jason Raphael Rambach
María Alejandra Sánchez Marín
Kripasindhu Sarkar
Alexander Schäfer
René Schuster
Mohamed Selim
M.Sc. Dennis Stumpf
Yongzhi Su
Xiaoying Tan
Aditya Tewari
André Luiz Brandão
Ahmet Firintepe
Sk Aziz Ali
Jilliam Maria Diaz Barros
Tewodros Amberbir Habtegebrial
Mina Ameli
Pramod Murthy
Consolidating Segmentwise Non-Rigid Structure from Motion
Consolidating Segmentwise Non-Rigid Structure from Motion
International Conference on Machine Vision Applications (MVA). IAPR Conference on Machine Vision Applications (MVA-2019) May 27-31 Tokyo Japan IAPR 2019 .
- Abstract:
- This paper introduces a new segmentwise technique which consolidates multiple principles for non-rigid structure from motion (NRSfM) into a single energy-based framework. The energy functional of our Consolidating Monocular Dynamic Reconstruction (CMDR) approach is optimised by non-linear least squares and includes terms allowing to define the deformation model and additional constraints simultaneously in the metric and trajectory spaces. The proposed method achieves high accuracy on several tested sequences while providing robustness and scalability due to the spatial scene segmentation and the new lifted spatial Laplacian term. CMDR is flexible and easy to implement, thanks to the unified optimisation framework. It allows for scenario-specific extensions and can be used for rapid prototyping of new NRSfM methods.