Multiresolution analysis and matrix factorization are foundational tools in computer vision. In
this work, we study the interface between these two distinct topics and obtain techniques to
uncover hierarchical block structure in symmetric matrices--an important aspect in the
success of many vision problems. Our new algorithm, the incremental multiresolution matrix
factorization, uncovers such structure one feature at a time, and hence scales well to large
matrices. We describe how this multiscale analysis goes much farther than what a direct" …

Algorithm 1 adds one extra row/column is to a given MMF, and clearly, the incremental
procedure can be repeated as more and more rows/columns are added. Algorithm 3
summarizes this incremental factorization for arbitrarily large and dense matrices. It has two
components: an initialization on some randomly chosen small block (of size m× m) of the
entire matrix C; followed by insertion of the remaining m− m rows/columns using Algorithm 1
in a streaming fashion The initialization entails computing a batch-wise MMF on this small …