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Liat Negrin, an employee at OrCam, wears a device
made by the company that consists of a camera and a small computer.
Orcam
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JERUSALEM — Liat Negrin, an Israeli who has been visually impaired since childhood, walked into a grocery store here recently, picked up a can of vegetables and easily read its label using a simple and unobtrusive camera attached to her glasses.
Ms. Negrin, who has coloboma, a birth defect that perforates a structure
of the eye and afflicts about 1 in 10,000 people, is an employee at
OrCam, an Israeli start-up that has developed a camera-based system
intended to give the visually impaired the ability to both “read” easily
and move freely.
Until now reading aids for the visually impaired and the blind have been
cumbersome devices that recognize text in restricted environments, or,
more recently, have been software applications on smartphones that have
limited capabilities.
In contrast, the OrCam device is a small camera worn in the style of
Google Glass, connected by a thin cable to a portable computer designed
to fit in the wearer’s pocket. The system clips on to the wearer’s
glasses with a small magnet and uses a bone-conduction speaker to offer
clear speech as it reads aloud the words or object pointed to by the
user.
The system is designed to both recognize and speak “text in the wild,” a
term used to describe newspaper articles as well as bus numbers, and
objects as diverse as landmarks, traffic lights and the faces of
friends.
It currently recognizes English-language text and beginning this week will be sold through the company’s Web site
for $2,500, about the cost of a midrange hearing aid. It is the only
product, so far, of the privately held company, which is part of the
high-tech boom in Israel.
The device is quite different from other technology that has been
developed to give some vision to people who are blind, like the artificial retina
system called Argus II, made by Second Sight Medical Products. That
system, which was approved by the Food and Drug Administration in
February, allows visual signals to bypass a damaged retina and be
transmitted to the brain.
The OrCam device is also drastically different from Google Glass, which
also offers the wearer a camera but is designed for people with normal
vision and has limited visual recognition and local computing power.
OrCam was founded several years ago by Amnon Shashua,
a well-known researcher who is a computer science professor at Hebrew
University here. It is based on computer vision algorithms that he has
pioneered with another faculty member, Shai Shalev-Shwartz, and one of his former graduate students, Yonatan Wexler.
“What is remarkable is that the device learns from the user to recognize a new product,” said Tomaso Poggio,
a computer scientist at M.I.T. who is a computer vision expert and with
whom Dr. Shashua studied as a graduate student. “This is more complex
than it appears, and, as an expert, I find it really impressive.”
The advance is the result of both rapidly improving computing processing
power that can now be carried comfortably in a wearer’s pocket and the
computer vision algorithm developed by the scientists.
On a broader technology level, the OrCam system is representative of a
wide range of rapid improvements being made in the field of artificial
intelligence, in particular with vision systems for manufacturing as
well as fields like autonomous motor vehicles. (Dr. Shashua previously
founded Mobileye, a corporation that supplies camera technology
to the automobile industry that can recognize objects like pedestrians
and bicyclists and can keep a car in a lane on a freeway.)
Speech recognition is now routinely used by tens of millions of people
on both iPhones and Android smartphones. Moreover, natural language
processing is making it possible for computer systems to “read”
documents, which is having a significant impact in the legal field,
among others.
There are now at least six competing approaches in the field of computer
vision. For example, researchers at Google and elsewhere have begun
using what are known as “deep learning” techniques that attempt to mimic
biological vision systems. However, they require vast computing
resources for accurate recognition.
In contrast, the OrCam technique, which was described in a technical paper
in 2011 by the Hebrew University researchers, offers a reasonable
trade-off between recognition accuracy and speed. The technique, known
as Shareboost, is distinguished by the fact that as the number of
objects it needs to recognize grows, the system minimizes the amount of
additional computer power required.
“The challenges are huge,” said Dr. Wexler, a co-author of the paper and
vice president of research and development at OrCam. “People who have
low vision will continue to have low vision, but we want to harness
computer science to help them.”
Additionally the OrCam system is designed to have a minimal control
system, or user interface. To recognize an object or text, the wearer
simply points at it with his or her finger, and the device then
interprets the scene.
The system recognizes a pre-stored set of objects and allows the user to
add to its library — for example, text on a label or billboard, or a
stop light or street sign — by simply waving his or her hand, or the
object, in the camera’s field of view.
One of the key challenges, Dr. Shashua said, was allowing quick optical
character recognition in a variety of lighting conditions as well as on
flexible surfaces.
“The professional optical character readers today will work very well
when the image is good, but we have additional challenges — we must read
text on flexible surfaces like a hand-held newspaper,” he said.
Although the system is usable by the blind, OrCam is initially planning
to sell the device to people in the United States who are visually
impaired, which means that their vision cannot be adequately corrected
with glasses.
In the United States, 21.2 million people over the age of 18 have some
kind of visual impairment, including age-related conditions, diseases
and birth defects, according to the 2011 National Health Survey by the
U.S. National Center for Health Statistics. OrCam said that worldwide
there were 342 million adults with significant visual impairment, and
that 52 million of them had middle-class incomes.
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