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Factorization with Missing Data for 3D Structure Recovery Rui F. C. Guerreiro and Pedro M. Q. Aguiar
 

Summary: Factorization with Missing Data for 3D Structure Recovery
Rui F. C. Guerreiro and Pedro M. Q. Aguiar
Institute for Systems and Robotics / Instituto Superior T´ecnico, Lisboa, Portugal
Email: {rfcg,aguiar}@isr.ist.utl.pt
Abstract--Matrix factorization methods are now widely used to
recover 3D structure from 2D projections [1]. In practice, the ob-
servation matrix to be factored out has missing data, due to the
limited field of view and the occlusion that occur in real video se-
quences. In opposition to the optimality of the SVD to factor out
matrices without missing entries, the optimal solution for the miss-
ing data case is not known. In reference [2] we introduced subopti-
mal algorithms that proved to be more efficient than previous ap-
proaches to the factorization of matrices with missing data. In this
paper we make an experimental analysis of the algorithms of [2]
and demonstrate their performance in virtual reality and video
compression applications. We conclude that these algorithms are:
i) adequate to the amount of missing entries that may occur when
processing real videos; ii) robust to the typical level of noise in
practical applications; and iii) computationally as simple as the
factorization of matrices without missing entries.

  

Source: Aguiar, Pedro M. Q. - Institute for Systems and Robotics (Lisbon)

 

Collections: Engineering