|
Topic Name: Visual Clutter: Legibility with the screen is measured
Category: Biodesign
Research persons: Ruth Rosenholtz & Her Team
Location: Massachusetts Institute of Technology,Cambridge, MA 02139-4307, United States
Details
A software is able automatically to evaluate the legibility of visual on a
screen. The objective is better to include/understand how the man perceives what
it sees. A team of researchers of MIT developed a process allowing to evaluate
the level of legibility of a visual representation diffused via a screen. Taking
the form of an accessible software application free on line, this innovation is
the fruit of a reflexion around the legibility report/ratio and effectiveness of
a given posting. This bond revêt a paramount importance when it is a question of
identifying a symbol or to sail within a Web page for example.
To measure the legibility of a posting
Taken along by Ruth Rosenholtz, person in charge for the department brain and
cognitive sciences with MIT, these specialists in optics succeeded in defining a
scale of visual value taking of account the color of the posted data, the
contrast and the orientation of these last. The step of this group of research
aims indeed at a better comprehension of the factors influencing the capacity to
identify and find an element of posting. “There is a lack as for the
comprehension of what is visual nonreadable, which are its characteristics,
which are the factors which makes it not easily perceptible”, Ruth Rosenholtz
indicates. With more close to the human visibility
Authors of a publication on this subject in the review
Newspaper of Vision, the American academics stated to have
established a correlation between time necessary to find a symbol on a
geographical chart and the level of legibility measured by their software. By
confronting the results obtained by this application to the opinions of a panel
of 20 people questioned on the legibility of several documents, the application
would again have shown its relevance.
The next stage of this research should consist in placing the software at the
disposal of visual originators in order to obtain a return user.
Measuring Visual Clutter
Why Measure Clutter?
Visual clutter can interfere with searching for a threat in a baggage x-ray, or
a document on your real or virtual desktop. Driving performance is degraded in
the presence of "road clutter," and clutter can interfere with information
gathering and decision making in complex information visualizations such as maps
and web pages.
A reliable measure of clutter might help inform designers, or help optimize
visual clutter in situations in which there can be no human designer in the
loop, e.g. when displays change dynamically. In situations in which one has
minimal control over the level of clutter, e.g. for road clutter or clutter in
baggage x-rays, a measure of visual clutter might allow for system alerts to
signal that performance might be impaired.
Furthermore, a measure of visual clutter should also be useful to the human
vision community, by helping us to generalize models of visual search to images
such as natural scenes. A measure of visual clutter might replace the notion of
"set size", i.e. the number of objects in the scene, as this is difficult to
measure for natural scenes.
Measures of Visual Clutter: Some Intuitions
We have developed and tested two measures of visual clutter: the Feature
Congestion measure, and the Subband Entropy measure.
Feature Congestion measure: This measure of visual clutter is based on
the common experience of going to put a note on a colleague's desk. If the desk
is uncluttered, it's easy to find a place to put the note where we are confident
our colleague will notice it. However, if the desk is cluttered, we tend not to
be confident they will notice the note, and perhaps will leave the note on a
chair so they will spot it.
This suggests that clutter is related to the difficulty in adding an
attention-grabbing item to a display. Visual search models typically attempt to
predict the difficulty of searching for a particular target among particular
destructors. However, our
Feature Congestion: a
measure of display clutter."SIGCHI 2005, 761-770, 2005.
Software
How cluttered is my display?
MATLAB code for generating
color and contrast "clutter maps".
About Researchers:
Ruth Rosenholtz
Principal Research Scientist
Dept. of Brain and Cognitive Sciences
Massachusetts Institute of Technology
46-4115D
Cambridge, MA 02139-4307
617-324-0269
rruth_(at)_mit_(dot)_edu
Research interests of Ruth Rosenholtz: Human vision, particularly
visual search/attention
and texture perception.
Also the application of human vision research to
user interface design
and information visualization, including the study of visual clutter. My
meta-level interest is in thinking of the visual system as
statistician.
Past and Present Research Focus
Texture and
visual search
Visual search in cluttered environments -- what is clutter?
Models for visual search and "popout."
"Asymmetries" in visual search
Effects of background color on color search
Models for texture segmentation.
Segmenting images into textured and non-textured regions.
Application of human vision research to
user interface design
and information visualization
Searching the web with enhanced thumbnails.
Document browsing aids.
"Doodle" icons to aid in searching for a computer file.
Tools for visualizing a large document on a small display.
Understanding clutter.
Shape from texture
Computer vision algorithm for shape from texture and an ideal observer for human
vision.
A texture "aperture effect" and texture transparency.
Shape from texture for multiple textures.
Do we use isotropy or homogeneity as a cue for shape from texture?
Perceptually-based image compression and image quality
Reducing blocking effects in block transform coded images.
Perceptually based coding of still images.
Assorted other work
Affine structure and photometry.
Mechanisms of character recognition.
Related papers and presentations.
|
