FULL STORY
As the researchers explain,
humans can perceive stylistic similarity between objects that transcends
structure and function. For example, we can see a common style such as
Danish modern' in both a table and chair, though they have different
structures. Until now, machines have found it difficult to do the same.
Credit: UMass Amherst
Computer scientists from the University
of Massachusetts Amherst led by Evangelos Kalogerakis unveiled a new
software modeling program that uses sophisticated geometric matching and
machine learning to successfully mimic the human perception of style,
giving users powerful new tools to compare the style similarity of
three-dimensional (3D) objects.
Kalogerakis and his doctoral student Zhaoliang Lun in the College of
Information and Computer Sciences at UMass Amherst, with Alla Sheffer
from the University of British Columbia, presented their new algorithm
at one of the world's largest computer graphics conferences, the annual
Association for Computing Machinery's (ACM) Special Interest Group on
Computer Graphics and Interactive Techniques (SIGGRAPH) 2015, going on
this week in Los Angeles.
As the researchers explain, humans can perceive stylistic similarity
between objects that transcends structure and function. For example, we
can see a common style such as "Danish modern" in both a table and
chair, though they have different structures. Until now, machines have
found it difficult to do the same.
The new first-of-its-kind structure-transcending software can benefit
several computer graphics applications, Kalogerakis says. "We hope that
future 3D modeling software tools will incorporate our approach to help
designers create aesthetically and stylistically plausible 3D scenes,
such as indoor environments. Our approach could also be used by 3D
search engines on the web to help users retrieve 3D models according to
style tags. For example, if you wanted to search for 'Gothic church,'
our software tools can help. It will be exciting to see all the ways
people will find to use it."
Kalogerakis is an expert in developing computational techniques that
analyze and synthesize visual content, focusing on machine learning
algorithms that help people to create 3D models. To develop the new
software, he and colleagues drew on observations about style similarity
in art history and appraisal literature, which provided geometric
elements including shape, proportion and lines, and visual motifs as key
indicators of stylistic similarity.
They also used crowdsourcing to present object's style comparisons to
more than 2,500 people, including artists, who volunteered via Amazon
Mechanical Turk on the Internet. This yielded more than 50,000 responses
on seven structurally diverse categories, buildings, furniture, lamps,
coffee sets, architectural pillars, cutlery and dishes. The human
respondents agreed on style similarity on average 85 percent of the
time.
As for the software tool, the researchers evaluated it by comparing
its responses to the human evaluations and found that it achieves "a
surprising agreement rate" of 90 percent, Kalogerakis reports, "making
it your next-to-best alternative style expert for providing you with
suggestions of objects to populate your home, dining table, or virtual
reality environment."
As he explains, computer graphics algorithms help people create
movies, visual effects, games, virtual and augmented reality
environments. They are also useful in manufacturing real objects and
designing architectural scenery. More generally, the new algorithm is
expected to be useful to those exploring databases of digital
representations of buildings, pillars and other objects according to
style attributes for designing virtual or real environments, creating
content for a computer game, and populating an augmented reality
environment with virtual objects.
Computer algorithms also run in the background on many devices, as
well, he says, such as spell and grammar checkers, programs that deblur
photographs or focus on faces. Robots run computer algorithms to
recognize their environment to move around and pick up objects. Online
search engines run computer algorithms to help users find documents,
pictures and videos.
SIGGRAPH members include researchers, developers and users from the
technical, academic, business and art communities who use computer
graphics and interactive techniques. ACM is the world's largest
educational and scientific computing society for educators, researchers
and professionals to inspire dialogue, share resources and address the
field's challenges.
Story Source:
The above post is reprinted from
materials provided by
University of Massachusetts at Amherst.
Note: Materials may be edited for content and length.
Comments
Post a Comment