2024-03-29T12:18:53Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1552322017-09-20T00:54:44Zcom_10261_106com_10261_4col_10261_863
Non-rigid structure from motion for complex motion
Molina Mellado, Sergi
Agudo, Antonio
Moreno-Noguer, Francesc
Low-rank models
Clustering
Non-rigid reconstruction
Monocular vision
Master’s Thesis: Master’s degree in Automatic Control and Robotics. Treball de Fi de Master has been carried out at: Escola Tècnica Superior d’Enginyeria Industrial de Barcelona of Universitat Politècnica de Catalunya.
Recovering deformable 3D motion from temporal 2D point tracks in a monocular video is an open problem with many everyday applications throughout science and industry, or the new augmented reality. Recently, several techniques have been proposed to deal the problem called Non-Rigid Structure from Motion (NRSfM), however, they can exhibit poor reconstruction performance on complex motion. In this project, we will analyze these situations for primitive human actions such as walk, run, sit, jump, etc. on different scenarios, reviewing first the current techniques to finally present our novel method. This approach is able to model complex motion into a union of subspaces, rather than the summation occurring in standard low-rank shape methods, allowing better reconstruction accuracy. Experiments in a wide range of sequences and types of motion illustrate the benefits of this new approach.
2017-09-19T07:21:30Z
2017-09-19T07:21:30Z
2016
2017-09-19T07:21:31Z
tesis de maestría
http://hdl.handle.net/10261/155232
eng
Publisher's version
Sí
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
openAccess
Universidad Politécnica de Cataluña