Since “selfie” was named the Oxford Dictionaries word of the year in 2013, these digital self-portraits have only become more prolific. They’re taken practically everywhere by everyone, from parents to presidents and astronauts to macaques. But with more selfies come worse selfies — and more amateurs who haven’t quite mastered the method.
In yet another example of science solving real-world problems, researchers from the University of Waterloo have created a smartphone app that uses an algorithm to guide the perfect selfie.
To find the parameters of a perfect selfie, researchers Dan Vogel and Qifan Li asked thousands of users on Mechanical Turk to review hundreds of artificial selfies, which they generated from 3D digital scans. The Turks were asked to rate the selfies, each of which differed slightly in composition, labeling them as good, bad, or meh.
“We focused on basic principles of composition,” Vogel, a professor of computer science at the University of Waterloo, told Digital Trends, “face size, face position, and lighting direction. These parameters are very fundamental to any photograph. On a technical level, we could also control them very accurately in the thousands of ‘virtual’ selfies we created using 3D computer graphics, and we could recognize them in real time when a person was taking a selfie [by] using computer vision techniques.”
By mathematically modeling the selfie scores, Vogel and Li were able to create an algorithm that can guide a user in how to move his or her camera to take the best selfie. To demonstrate that the algorithm was indeed a good director, the researchers asked real people to take selfies under the app’s guidance and again asked Mechanical Turks to rate them. With the algorithm’s assistance, selfie takers saw a 26-percent improvement in their photos, according to the study.
The researchers are now considering ways to commercialize their technology, both as an app for selfies and to guide photos of other kinds.
“We’ve talked about applying our virtual photo methodology to photos of products for buy-and-sell auction sites like eBay, or real estate photos, vacation landscapes, you name it,” Vogel said. “It really comes down to generating thousands of highly controlled photographs than can be rated by thousands of people so we can generate mathematical models.”
Google has been finding more ways to make Gemini a part of your daily routine, from putting together playlists to ordering groceries through your favorite apps. Now it's expanding those capabilities to more services, with Google Search joining in, too.
The company has announced a new Connected Apps Platform that makes it easier for developers to bring their services to both Gemini and Search. Alongside this, Google is adding new partners to its growing lineup, bringing more of the apps people already use into its AI ecosystem.
In the broad context of AI and its perceived harms, health and medical risks often pop up in the conversation. The warnings even come from frontier AI labs, such as ChatGPT-maker OpenAI and Anthropic, both of which have warned about misusing AI to cook up bioweapons. Security experts have already spotted a few such incidents in the wild, especially with the usage of AI models without any solid guardrails.
Well, it appears that the risks run deeper. As per an analysis appearing in the British Medical Journal (BMJ), AI bots are now being deployed to influence public policies governing health risks to citizens. In this instance, an attempt was made using AI bots to thwart regulations that aim to restrict the sale of disposable vapes, all while disguising the manipulation efforts as a response from real humans.
What if checking your drinking water for dangerous chemicals were as simple as plugging a tiny gadget into your smartphone? Researchers in Japan have developed a compact sensor that could make that possible, potentially bringing sophisticated water contamination testing out of expensive laboratories and into people's hands.
Scientists at the Okinawa Institute of Science and Technology (OIST) have created a portable device capable of detecting extremely low concentrations of PFAS, commonly known as "forever chemicals." The findings were published in the journal Biosensors and Bioelectronics, which demonstrate how an inexpensive sensor and a smartphone could make identifying potentially harmful chemicals in water a lot easier.