Domain adaptation is one of the most challenging tasks of modern data analytics. If the
adaptation is done correctly, models built on a specific data representation become more …

In this paper, we present a unified framework for the rigid and nonrigid point set registration
problem in the presence of significant amounts of noise and outliers. The key idea of this …

Graph matching (GM) is a fundamental problem in computer science, and it plays a central
role to solve correspondence problems in computer vision. GM problems that incorporate …

As a fundamental problem in pattern recognition, graph matching has applications in a
variety of fields, from computer vision to computational biology. In graph matching, patterns …

This paper presents an approach for attributed scattering center (ASC) matching with
application to synthetic aperture radar (SAR) automatic target recognition (ATR). A statistics …

We investigate how to discover all common visual patterns within two sets of feature points.
Common visual patterns generally share similar local features as well as similar spatial …

In graph-based structural pattern recognition, the idea is to transform patterns into graphs
and perform the analysis and recognition of patterns in the graph domain—commonly …

We address the problem of model-based object recognition. Our aim is to localize and
recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D …

We present an adaptation algorithm focused on the description of the data changes under
different acquisition conditions. When considering a source and a destination domain, the …

Graph matching has received persistent attention over decades, which can be formulated as
a quadratic assignment problem (QAP). We show that a large family of functions, which we …