This paper proposes a method for capturing the performance
of a human or an animal from a multi-view video
sequence. Given an articulated template model and silhouettes
from a m...
Juergen Gall (BIWI, ETH Zurich), Carsten Stoll (Ma...
Efficient and accurate fitting of Active Appearance
Models (AAM) is a key requirement for many applications.
The most efficient fitting algorithm today is Inverse Compositional
...
Brian Amberg (University of Basel), Andrew Blake (...
This article proposes a novel similarity measure between
vector sequences. Recently, a model-based approach was
introduced to address this issue. It consists in modeling
each se...
Over the past decade, multiple-instance learning (MIL)
has been successfully utilized to model the localized
content-based image retrieval (CBIR) problem, in which a
bag corresp...
Wu-Jun Li (Hong Kong University of Science and Tec...
This paper covers a fundamental problem of local phase
based signal processing: the isotropic generalization of the
classical 1D analytic signal to two dimensions. The well
know...
Lennart Wietzke (Kiel University), Gerald Sommer (...
Statistical approaches for building non-rigid deformable
models, such as the Active Appearance Model (AAM), have
enjoyed great popularity in recent years, but typically require
...
Akshay Asthana (Australian National University), R...
In this paper, we present an enhanced Pictorial Struc-
ture (PS) model for precise eye localization, a fundamen-
tal problem involved in many face processing tasks. PS is
a comp...
Xiaoyang Tan (Nanjing University of Aeronautics an...
We present a new method for detecting interest points
using histogram information. Unlike existing interest point
detectors, which measure pixel-wise differences in image
intens...
Wei-Ting Lee (National Tsing Hua University), Hwan...
Detection of visually salient image regions is useful for
applications like object segmentation, adaptive compression,
and object recognition. In this paper, we introduce
a meth...
Radhakrishna Achanta, Sheila S. Hemami, Francisco ...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...