Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Motion Segmentation from Pairwise Matches   In this paper we address a classification problem that has not been
considered before, namely motion segmentation given pairwise matches only. Our
contribution to this unexplored task is a novel formulation of motion
segmentation as a two-step process. First, motion segmentation is performed on
image pairs independently. Secondly, we combine independent pairwise
segmentation results in a robust way into the final globally consistent
segmentation. Our approach is inspired by the success of averaging methods. We
demonstrate in simulated as well as in real experiments that our method is very
effective in reducing the errors in the pairwise motion segmentation and can
cope with large number of mismatches.

21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin