Continuous Mobile Vision Takes a Step Forward
You might not be aware of the term “continuous mobile vision,” but I’ll bet there’s a good chance you are aware of one of the scenarios it could enable.
Remember the concept, bandied about in recent years, of technology that can remind you of a person’s name once her or his face has been detected? Yeah, that one. I’m sure that most of us could make use of it once in a while.
The problem, though, is that image sensing takes lots of energy. That’s because modern image sensors lack energy proportionality. They’re power-hungry. That’s fine when a high-resolution, high-frame-rate image is desired. But even when you’re not seeking images of that quality, today’s image sensors still consume a lot of power.
Someday soon, though, things could change for the better. That’s the premise behind the paper Energy Characterization and Optimization of Image Sensing Toward Continuous Mobile Vision" href="http://www.ruf.rice.edu/~mobile/publications/likamwa2013mobisys1.pdf" target="_blank">Energy Characterization and Optimization of Image Sensing Toward Continuous Mobile Vision” href=”http://research.microsoft.com/apps/pubs/default.aspx?id=194140″ target=”_blank”>Energy Characterization and Optimization of Image Sensing Toward Continuous Mobile Vision, which has been accepted for presentation during MobiSys 2013, the 11th International Conference on Mobile Systems, Applications and Services, being held June 25-28 in Taipei, Taiwan.
The paper was written by Robert LiKamWa and Lin Zhong of Rice University and Microsoft Research Redmond, along with Bodhi Priyantha, Matthai Philipose, and Paramvir (Victor) Bahl of Microsoft Research Redmond.
Bahl, a principal researcher and manager of the Mobility and Networking Research group, spoke June 11 during the MIT Technology Review Mobile Summit 2013, held June 10-11 in San Francisco, discussing the technology behind the MobiSys paper, and he underscored the new area being explored by him and his colleagues.
“Our industry has been focused on building small, higher-resolution image sensors for decades,” he said. “We believe that we are the first to look at systems-level optimizations for improving their energy consumption. We believe the techniques we have designed are fundamental, in that they will stand the test of time.”
The vision behind this work was delivered a year ago, during the Mobile Cloud Computing and Services workshop, in a paper titled video website for the event.