419 research outputs found
Intelligent visual media processing: when graphics meets vision
The computer graphics and computer vision communities have been working closely together in recent
years, and a variety of algorithms and applications have been developed to analyze and manipulate the visual media
around us. There are three major driving forces behind this phenomenon: i) the availability of big data from the
Internet has created a demand for dealing with the ever increasing, vast amount of resources; ii) powerful processing
tools, such as deep neural networks, provide e�ective ways for learning how to deal with heterogeneous visual data;
iii) new data capture devices, such as the Kinect, bridge between algorithms for 2D image understanding and
3D model analysis. These driving forces have emerged only recently, and we believe that the computer graphics
and computer vision communities are still in the beginning of their honeymoon phase. In this work we survey
recent research on how computer vision techniques bene�t computer graphics techniques and vice versa, and cover
research on analysis, manipulation, synthesis, and interaction. We also discuss existing problems and suggest
possible further research directions
Quantitative Analysis of Saliency Models
Previous saliency detection research required the reader to evaluate
performance qualitatively, based on renderings of saliency maps on a few
shapes. This qualitative approach meant it was unclear which saliency models
were better, or how well they compared to human perception. This paper provides
a quantitative evaluation framework that addresses this issue. In the first
quantitative analysis of 3D computational saliency models, we evaluate four
computational saliency models and two baseline models against ground-truth
saliency collected in previous work.Comment: 10 page
Mesh saliency via spectral processing
We propose a novel method for detecting mesh saliency, a perceptuallybased
measure of the importance of a local region on a 3D surface mesh.
Our method incorporates global considerations by making use of spectral
attributes of the mesh, unlike most existing methods which are typically
based on local geometric cues. We first consider the properties of the log-
Laplacian spectrum of the mesh. Those frequencies which show differences
from expected behaviour capture saliency in the frequency domain. Information
about these frequencies is considered in the spatial domain at multiple
spatial scales to localise the salient features and give the final salient
areas. The effectiveness and robustness of our approach are demonstrated
by comparisons to previous approaches on a range of test models. The benefits
of the proposed method are further evaluated in applications such as
mesh simplification, mesh segmentation and scan integration, where we
show how incorporating mesh saliency can provide improved results
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
We propose a fully automatic method for fitting a 3D morphable model to
single face images in arbitrary pose and lighting. Our approach relies on
geometric features (edges and landmarks) and, inspired by the iterated closest
point algorithm, is based on computing hard correspondences between model
vertices and edge pixels. We demonstrate that this is superior to previous work
that uses soft correspondences to form an edge-derived cost surface that is
minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic
- …