Computer vision lessons from the video game industry

Computer vision offers great promise, as algorithms are maturing rapidly and processing power continues to grow exponentially. But today’s approach to computer vision software development—hiring a team of PhDs to hack OpenCV—is not scalable, and represents a major bottleneck to mass deployment of vision-enabled products, suggests Paul Kruszewski, President of WRNCH.

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Computer vision offers great promise, as algorithms are maturing rapidly and processing power continues to grow exponentially. But today’s approach to computer vision softwaredevelopment—hiring a team of PhDs to hack OpenCV—is not scalable, and represents a major bottleneck to mass deployment of vision-enabled products, suggests Paul Kruszewski, President of WRNCH.

The video game industry, he explained in a May 2016 Embedded Vision Summit presentation, faced similar challenges in the early 2000s, when it became impractical for game developers to write an entire game engine from scratch. In his presentation, Kruszewski provides lessons that the computer vision industry can learn from the video game industry, and predicts how computer vision software development will evolve to enable creation of thousands of new vision-enabled products. He also shares ways that managers and entrepreneurs can avoid the most serious pitfalls of vision software development today.

Check out the full presentation here:

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