Tag Photos Automatically Using TagSense Mobile App

A new app called TagSense which is developed by students does photo tagging for the user. The new 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 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.

Bao 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.

[advt]By 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.

For 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.

The 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’ privacy.

The 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.

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

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