Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

The success of kernel methods has initiated the design of novel positive semidefinite
functions, in particular for structured data. A leading design paradigm for this is the …

Many shape and image processing tools rely on computation of correspondences between
geometric domains. Efficient methods that stably extract" soft" matches in the presence of …

Data-driven methods serve an increasingly important role in discovering geometric,
structural, and semantic relationships between shapes. In contrast to traditional approaches …

The algorithmic advancement of synchronizing maps is important in order to solve a wide
range of practice problems with possible large-scale dataset. In this paper, we provide …

In this work, we propose a combinative strategy based on regression and clustering for
solving point set matching problems under a Bayesian framework, in which the regression …

Feature-based object matching is a fundamental problem for many applications in computer
vision, such as object recognition, 3D reconstruction, tracking, and motion segmentation. In …

Due to its wide range of applications, matching between two graphs has been extensively
studied and remains an active topic. By contrast, it is still under-exploited on how to jointly …

This paper deals with the problem of estimating camera motion in the context of structure-
from-motion. We describe a pipeline that consumes relative orientations and produces …

This paper is concerned with jointly recovering n node variables {xi} 1≤ i≤ n from a
collection of pairwise difference measurements. Imagine we acquire a few observations …