Simpler cameras with embedded intelligence sounds like a good idea. In fact many vendors of smart cameras for machine vision are already heading in this direction, adding FPGAs, DSPs, and CPUs to their products so that their customers can build ever-more sophisticated systems without some of the software development needed for custom applications.
But wait! It seems that a group of 10-year-old kids is working on the same idea. Actually, it’s not quite the same idea since the kids are performing this task using a simple camera kit called BigShot (http://www.bigshotcamera.org/). The creator of BigShot is Shree Nayar, chairman of Columbia University’s computer-science department and director of the Computer Vision Laboratory.
BigShot is a build-it-yourself camera. It comes in a kit with less than 20 parts that snap and screw together simply. When it’s finished, users can peer through the transparent back and, with the help of labels preprinted on the plastic, show curious friends how the camera works. The labels point out the microprocessor, the memory chip, and other features that let this homemade device digitally capture, store, and reproduce images.
BigShot takes normal, panoramic, and even three-dimensional pictures. But the real point of the camera isn’t the photos. It’s to use the camera as an excuse to expose the kids to as many science and engineering concepts as possible.
Nayar worked with a group of contractors to flesh out his initial design and build the first set of working prototypes. He also worked with a group of undergraduate and graduate students at Columbia to develop the online educational materials, design the Bigshot website, and conduct the field tests.
So far there have been test sites in New York City, Bengaluru, India, and Vung Tao, Vietnam, where, the camera has served as a means for children of very different social and economic backgrounds to communicate and express themselves.
What can vendors and integrators of machine-vision products learn from such an undertaking? One lesson, perhaps, is that it is critical to educate young people in science and engineering and encourage some to follow these career paths.
Another is that simplicity and transparency help make technology a more useful tool--whether in education, manufacturing, security, biomedical research, or human relations.
In ways we may not yet recognize, the future success of such machine vision and image processing applications is already being secured by the interest, enthusiasm, and energy of 10-year olds fiddling with do-it-yourself cameras.