New Smartphone App Automatically Tags Photos

Sensors on location, surroundings, other phones nearby add context to a photo.

Graduate students Chaun Qin and Xuan Bao developed TagSense.

So much for tagging photographs with names, locations and activities yourself
– a new cell phone application can take care of that for you.

system works by taking advantage of the multiple sensors on a mobile phone, as
well as those of other mobile phones in the vicinity.

TagSense, the new app was developed by students from Duke University and the
University of South Carolina (USC) and unveiled at the ninth Association for
Computing Machinery's International Conference on Mobile Systems, Applications
and Services (MobiSys), being held in Washington, D.C.

our system, when you take a picture with a phone, at the same time it senses
the people and the context by gathering information from all the other phones
in the area," said Xuan Bao, a Ph.D. student in computer science at Duke who
received his master's degree at Duke in electrical and computer engineering.

and Chuan Qin, a visiting graduate student from USC, developed the app working
with Romit Roy Choudhury, assistant professor of electrical and computer
engineering at Duke’s Pratt School of Engineering. Qin and Bao are currently
involved in summer internships at Microsoft Research.

have many different kinds of sensors that you can take advantage of," Qin said. "They collect diverse information like sound, movement, location and light. By
putting all that information together, you can sense the setting of a photograph
and describe its attributes."

using information about the environment of a photograph, the students believe they
can achieve a more accurate tagging of a particular photograph than could be achieved
by facial recognition alone. Such information about a photograph's entirety
provides additional details that can then be searched at a later time.

example, the phone's built-in accelerometer can tell if a person is standing
still for a posed photograph, bowling or even dancing. Light sensors in the phone's
camera can tell if the shot is being taken indoors or outdoors on a sunny or cloudy
day. The sensors can also approximate environmental conditions – such as snow
or rain -- by looking up the weather conditions at that time and location. The
microphone can detect whether or not a person in the photograph is laughing, or
quiet. All of these attributes are then assigned to each photograph, the
students said.

pointed out that with multiple tags describing more than just a particular
person's name, it would be easier to not only organize an album of photographs
for future reference, but find particular photographs years later. With the
exploding number of digital pictures in the cloud and in our personal
computers, the ability to easily search and retrieve desired pictures will be
valuable in the future, he said.

for example, if you've taken a bunch of photographs at a party, it would be
easy at a later date to search for just photographs of happy people dancing," Qin said. "Or more specifically, what if you just wanted to find photographs
only of Mary dancing at the party and didn’t want to look through all the
photographs of Mary?"

added details of automatic tagging could help complement existing tagging
applications, according to senior researcher Roy Choudhury.

facial recognition programs continue to improve, we believe that the ability to
identify photographs based on the setting of the photograph can lead to a
richer, more detailed way to tag photographs," Roy Choudhury said. "TagSense
was compared to Apple's iPhoto and Google's Picasa, and showed that it can provide
greater sophistication in tagging photographs."

students envision that TagSense would most likely be adopted by groups of
people, such as friends, who would "opt in," allowing their mobile phone
capabilities to be harnessed when members of the group were together.
Importantly, Roy Choudhury added, TagSense would not request sensed data from
nearby phones that do not belong to this group, thereby protecting users'

experiments were conducted using eight Google Nexus One mobile phones on more
than 200 photos taken at various locations across the Duke campus, including
classroom buildings, gyms and the art museum.

current application is a prototype, and the researchers believe that a commercial
product could be available in a few years.

Nelakuditi, associate professor of computer science and engineering at USC, was
also a member of the research team. The research is supported by the National
Science Foundation. Roy Choudhury's Systems Networking Research Group is also supported
by Microsoft, Nokia, Verizon, and Cisco.