-By Meres J. Weche
"Our eyes are the equivalent of two cameras," says KAUST Electrical Engineering Assistant Professor, Bernard Ghanem. Much like cameras, human beings essentially record video. We then process theses images we intake to make decisions in our day-to-day lives. We know, for example, to stay away from a barking dog, not to touch a hot stove or not to walk onto unsafe surfaces. What if we could teach machines how to do the same thing? In fact, that's what computer vision and machine learning are all about - inputting visual stimuli, classifying the information and making a decision.
One industry in which computer vision is playing an important role today is the automotive sector -- with the advent of self-driving cars. Several auto manufacturers have already developed self-driving concept vehicles and are envisioning commercially viable models in the coming years. Google's self-driving cars are already set for circulating in the streets of California.
"The self-driving cars like Google have visual sensors," said Ghanem. Is the light red, green, or yellow? Because based on that there are traffic rules to follow. "But there are other sensors like range finders and other types of sensors that perceive how far certain objects are. The sensors can also determine exactly what those objects or obstacles are." When faced with a potential collision scenario, the autonomous driving technology in the vehicle must be able to differentiate between a pedestrian, a tree or another car when making a decision to veer the car in whichever direction.
Another company, Mobileye, specializing in computer vision will start introducing autonomous driving technology in certain brands of cars as early as next year for obstacle avoidance and for detecting when a person has started drifting from lane to lane.
Other industry applications
Computer scientists also use computer vision to assist governments, agencies, and corporations with such applications as surveillance, security and even marketing. For instance, several airports may use biometric technology to scan travelers' faces for identification purposes.
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