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Wednesday, May 2nd, 2012, 8:18 am

OpenCV, Android, and Hardware Limitations

Car navigation using computer vision algorithms/programs (as opposed to GPS/maps) is scarcely explored in the form of mobile applications. With many built-in cameras and increasing processing power/RAM it would be desirable to exploit — to the extent possible — whatever general-purpose devices have to offer while idle; single-purpose appliances like TomTom make less business sense nowadays and development frameworks for mobile platforms have become versatile enough to empower third-party developers. Based on conversations with colleagues, OpenCV and its many plugins should be somehow available for Android as well, albeit it may require some hacking and adaptation to the hardware at hand (high-end ARM for the most part).

If the goal is to make vehicles with cameras mounted onto them interpret a scene like humans do, then analysis of video sequences on mobile hardware (efficient applications) ought to be explored, with special emphasis on performance. C++ has little memory footprint and high efficiency. Contemporarily, resolution at a high capture rate is satisfactory enough for the task, but it is unclear whether a good algorithm that segments and tracks a scenes can keep up. A GPU-like processing power is available on some phones, but not all (drivers for non-x86 architectures are poor or scarce, too). MobileEye offers peripheral and assistive hardware for this reason, recognising the known caveats.Vuforia does augmented reality for mobile platforms and a company called ThirdSight also makes mobile applications with computer vision methodologies. Not so long ago (April 2010) it was reported that “development of new automobile safety features and military applications [...] could save lives.” The hardware is not specified in the report. To quote, “Snyder and his co-authors have written a program that uses algorithms to sort visual data and make decisions related to finding the lanes of a road, detecting how those lanes change as a car is moving, and controlling the car to stay in the correct lane.”

While purely automatic driving is currently verboten, computer-aided driving is legal and forms a growing trend. It need not involve any mechanics either, as it’s most about message-passing to a human (HCI).

One Response to “OpenCV, Android, and Hardware Limitations”

  1. svsik Says:

    I was recently working on the project of the Android application which used an OpenCV and the GPS. Despite fact of different approaches to implement a GPS, I didn’t manage to make them both working in the same time.

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