Do embedded processors shape applications, or is it the other way around?
A few years ago, after nearly two decades of evaluating and using embedded processors for DSP-intensive applications, my colleagues and I at Berkeley Design Technology Inc. realized that embedded computer vision applications were poised to benefit from the same type of virtuous circle that had previously enabled the proliferation of wireless communications and video compression algorithms.
With that vision starting to appear in volume applications, processor vendors are beginning to focus on embedded vision applications and to tune their processors for such apps, often by incorporating specialized co-processors designed for vision processing.
By reducing the number and severity of auto collisions, vision-based safety systems may be able to save many thousands of lives. Embedded vision also promises more-intuitive human-machine interaction—long the grail of consumer electronics. Imagine turning on your TV just by staring in its directiion for a few seconds; it then offers you a personalized menu of options, from which you choose using basic gestures. Market research company IMS Research estimates that by 2015, vision-enabled devices will be shipping at a rate of more than 3 billion units per year. (Read about many more embedded vision applications here.)
In some applications, vision functions will be simple and will be able to fit into existing processors (perhaps with a modest boost in clock rate or an additional core). But many of the most compelling embedded vision applications use very performance-hungry algorithms. Implementing those algorithms at low cost and low power consumption will require specialized processors. As a result, BDTI expects to see processor suppliers introducing more processors that are optimized for vision applications, and providing more application development support (such as optimized software libraries) for those apps.
Jeff Bier is the founder of the Embedded Vision Alliance and president of BDTI.
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