Thaindian News

London, June 12 (ANI): Do you often fail to notice a friend’s radical new haircut or miss a road sign showing a change in the speed limit? Well, then such ignorance to what should be apparent is something we all go through, and it is called change blindness.

And now, researchers at Queen Mary, University of London, have invented a unique spot-the-difference-style computer game in order to study it.

All they have to do is press the button and tell us exactly when they spot the change

“It’s the phenomenon where seemingly striking or obvious changes are not noticed,” the BBC quoted Milan Verma, a scientist at Queen Mary, as saying.

He and his colleagues are asking volunteers to play the game - which involves looking at a screen as it flashes between two images of the same scene.

“It flicks between a pre-change version and a post-change version of the scene. The volunteers simply have to press the button and tell us exactly when they spot the change,” explained Verma.

In fact, the Queen Mary team incorporate their biological findings into the design of robots - studying the basis of human vision and perception in order to artificially recreate it.

And Verma has said that this might be the first truly unbiased scientific study of change blindness.

“Previously, scientists have studied this by manually manipulating pictures,” he said.

In the current study, Verma and his colleague and supervisor, Professor Peter McOwan, created an algorithm that meant the computer “decided” how to change the image.

“This is, as far as I’m aware, the first time ever that artificial intelligence [AI] technology has been used to generate experimental stimuli to test human perception,” said McOwan.

“It brings together two interesting fields of study- AI and human visual intelligence,” he added.

The duo designed software that underlies the game’s ability to make a change to each image.

Verma describes this as a “genetic algorithm”-it essentially tells the computer to change the images in a process akin to evolution.

“It’s like a process of survival of the fittest. Darwin suggested that a fit individual is one that can best survive in its surroundings - like a moth that can camouflage with the bark of a tree,” explained Verma.

But in this case “fitness” is determined by the smallest difference between the pre- and post-change scenes, in terms of how attention grabbing they are.

The computer uses information about human attention and perception to generate two pictures that a person will view in exactly the same way; two images that are equally attention-grabbing.

This means the scientists get an accurate measure of how noticeable the change is and there is no “human bias” of the results.

The research is beginning to reveal where in a scene people direct their attention as well as what kinds of changes are more noticeable.

“It all boils down to contrast. So colour or orientation contrast; luminance contrast in terms of light and dark things that pop out. And it’s what’s easy to spot in terms of our viewing attention behaviour,” said Verma.

“So when we walk into a room, our eyes are attracted to a particular region and because we’re attending to that region, if there was a change made there, we would perhaps notice it more quickly,” he added.

The team has already had interest from companies that want to apply the findings to the design of safety notices and advertising displays - to grab our attention.

And there is potential for these results to be used in more clandestine ways- police or security services might take advantage of things that make people look.

“You can use these attention-grabbing principles to, for example, direct someone’s attention to a particular spot and that could be a spot where there is a camera. So you could take a photograph - a frontal image - that could be useful for police or security services,” explained Verma.

And he pointed out that they have already been applied by the emergency services.

The scientists have published their findings and described their unique approach in the journal Vision. (ANI)