SA-optimized multiple view smooth polyhedron representation NN

Mohamad Ivan Fanany, Itsuo Kumazawa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Simulated Annealing (SA) is a powerful stochastic search method that can produce very high quality solutions for hard combinatorial optimization problem. In this paper, we applied this SA method to optimize our 3D hierarchical reconstruction neural network (NN). This NN deals with complicated task to reconstruct a complete representation of a given object relying only on a limited number of views and erroneous depth maps of shaded images. The depth maps are obtained by Tsai-Shah shape-from-shading (SFS) algorithm. The experimental results show that the SA optimization enable our reconstruction system to escape from a local minima. Hence, it gives more exact and stable results with small additional computation time.

Original languageEnglish
Pages (from-to)306-310
Number of pages5
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2843
Publication statusPublished - 1 Dec 2003

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