Out of Shadows: New tech allows face recognition in utter darkness
Out of Shadows: New tech allows face recognition in utter
darkness
Published time: 28 Jul, 2015 18:31
German researchers have developed a new technology that
can identify a person in poor lighting or even in absolute darkness thus
potentially solving one of the main issues of the modern face recognition
systems.
Today’s facial recognition systems are based on matching
clean and well-lit photos taken in the broad light. This poses a problem for
law enforcement and security services when their object is in the shade.
However, a group of German scientists claim to have found
a solution to this as they develop a new type of face-recognition system that
analyzes a person’s thermal signature instead of relying on traditional
methods.
As a part of the new study, Saquib Sarfraz and Rainer
Stiefelhagen, two computer scientists from the Karlsruhe Institute of
Technology, Germany, created a system that analyzes mid- or far-infrared images
and matches them with the ordinary photos thus allowing the people’s faces to
be recognized.
However, such matching also poses a challenge for
computer systems as connection between human appearance in visible and infrared
light is highly nonlinear. The way human face emits thermal signatures when
infrared images are taken is absolutely different from the way the face
reflects light during a regular photo session.
Additionally, thermal emissions vary depending on the
environment temperature, temperature of the skin, person’s activity level or
even a change of expression.
Besides, the images taken by infrared cameras usually
have much lower resolution than normal photos. All these factors make the
matching of two types of images a challenging task.
The research team managed to overcome this difficulty by
using the so-called deep neural network system.
Deep neural network is a computer system designed to
imitate the functioning of a human brain. It can make connections and draw
conclusions based on complex sets of factors provided that a large enough
dataset is available for the system.
However, such smart system still needs a vast bank of
both infrared and visible light images allowing it to make comparisons and
“learn.” For their study, German researchers used the University of Notre Dame
set that contains a significant number of both types of images, including
people shot with different facial expressions, under different lightning
conditions and multiple images of the same person over a certain time period.
The data set used in the study consisted of 4.585 both
infrared and visible light images of 82 people. For the research, the
scientists divided the set into two parts and used the images of the first 41
people to “train” their system and the images of the rest 41 people to test it.
The results of the experiment showed that the new system
considerably surpasses its existing counterparts. “The presented approach
improves the state-of-the-art by more than 10 percent,” Sarfraz and
Stiefelhagen said as quoted by the MIT Technology Review.
Additionally, the system is capable of matching the
images and recognizing a face in just 35 milliseconds. “This is therefore, very
fast and capable of running in real-time at about 28 fps,” the researchers say.
However, the development of the technology is only at the
initial stages so it is far from perfect as its accuracy reaches only about 80%
in case when the system has many visible light images in its database to
compare to the thermal image. With only one visible image available, the
accuracy of the system falls to 55%.
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