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Researchers are developing a retinal implant that works with camera-equipped smart glasses and a microcomputer that may help blind people in getting an artificial vision. “Our system is designed to give blind people a form of artificial vision by using electrodes to stimulate their retinal cells,” said researcher Diego Ghezzi from the Ecole Polytechnique Federale de Lausanne in Switzerland.
The camera embedded in the smart glasses captures images in the wearer’s field of vision and sends the data to a microcomputer placed in one of the eyeglasses’ end-pieces. The microcomputer turns the data into light signals which are transmitted to electrodes in the retinal implant, according to a paper published in Communication Materials. The electrodes then stimulate the retina in such a way that the wearer sees a simplified, black-and-white version of the image.
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This simplified version is made up of dots of light that appear when the retinal cells are stimulated. However, wearers must learn to interpret the many dots of light in order to make out shapes and objects. Two parameters are used to measure vision — the field of vision and resolution.
For the study, the engineers, therefore, used these same two parameters to evaluate their system. The retinal implants they developed, the system that has not yet been tested on humans, contain 10,500 electrodes, with each one serving to generate a dot of light. (IANS/SP)
People with visual impairments often face difficulty to understand memes, but now researchers have developed a method to automatically identify memes and apply pre-written templates to add descriptive alt text, making them intelligible via existing assistive technologies.
The study was presented at the ACCESS conference in Pittsburgh, US.
Visually impaired people use social media like everyone else, often with the help of screen reader software. But that technology falls short when it encounters memes, which don’t include alternate text, or alt text, to describe what’s depicted in the image.
“Memes are images that are copied and then overlaid with slight variations of text. They are often humorous and convey a shared experience, but “if you’re blind, you miss that part of the conversation,” said study researcher Cole Gleason from Carnegie Mellon University in US.
Memes largely live within social media platforms that have barriers to adding alt text.
Twitter, for example, allows people to add alt text to their images, but that feature isn’t always easy to find. Of 9 million tweets the researchers examined, one million included images and, of those, just 0.1 per cent included alt text.
Researchers said that basic computer vision techniques make it possible to describe the images underlying each meme, whether it be a celebrity, a crying baby, a cartoon character or a scene such as a bus upended in a sinkhole.
Optical character recognition techniques are used to decipher the overlaid text, which can change with each iteration of the meme.
For each meme type, it’s only necessary to make one template describing the image, and the overlaid text can be added for each iteration of that meme.
But writing out what the meme is intended to convey proved difficult.
“It depended on the meme if the humor translated. Some of the visuals are more nuanced, and sometimes it’s explicit and you can just describe it,” Gleason said.
The team also created a platform to translate memes into sound rather than text. Users search through a sound library and drag and drop elements into a template.
This system was made to translate existing memes and convey the sentiment through music and sound effects.
“One of the reasons we tried the audio memes was because we thought alt text would kill the joke, but people still preferred the text because they’re so used to it,” Gleason said.
The researchers are currently working on related projects, including a browser extension for Twitter that attempts to add alt text for every image and could include a meme system. (IANS)