ICCV 2011

ICCV 2011

ICCV Paper on Subgraph Preconditioning

Today Yong-Dian Jian will present our ICCV 2011 paper on speeding up 3D reconstruction methods, which can be phrased as an optimization problem on a factor graph, by finding a tractable subgraph to precondition the original problem, as illustrated in the figure.

Generalized Subgraph Preconditioners for Large-Scale Bundle Adjustment,

Yong-Dian Jian, Doru Balcan, and Frank Dellaert, IEEE International Conference on Computer Vision (ICCV), 2011

Abstract

We present a generalized subgraph preconditioning (GSP) technique to solve large-scale bundle adjustment problems efficiently. In contrast with previous work which uses either direct or iterative methods as the linear solver, GSP combines their advantages and is significantly faster on large datasets. Similar to [11], the main idea is to identify a sub-problem (subgraph) that can be solved efficiently by sparse factorization methods and use it to build a preconditioner

for the conjugate gradient method. The difference is that GSP is more general and leads to much more effective preconditioners. We design a greedy algorithm to build subgraphs which have bounded maximum clique size in the

factorization phase, and also result in smaller condition numbers than standard preconditioning techniques. When applying the proposed method to the “bal” datasets [1], GSP displays promising performance.

ICCV 2011 is the premier international conference on computer vision, held this year in Barcelona, Spain.

Wednesday, November 9, 2011

Dataset courtesy of Sameer Agarwal et al., see their 2010 ECCV paper