The project resulted from a collaboration between researchers led by Professor Tsachy Weissman, and three high school students who interned in his lab.
The researchers asked people to compare images produced by a traditional compression algorithm that shrink huge images into pixilated blurs to those created by humans in data-restricted conditions – text-only communication, which could include links to public images. In many cases, the products of human-powered image sharing proved more satisfactory than the algorithm's work. The researchers will present their work at the 2019 Data Compression Conference.
"Almost every image compressor we have today is evaluated using metrics that don't necessarily represent what humans value in an image," said Irena Fischer-Hwang, an EE grad student and co-author of the paper. "It turns out our algorithms have a long way to go and can learn a lot from the way humans share information."
The project resulted from a collaboration between researchers led by Tsachy and three high school students who interned in his lab.
"Honestly, we came into this collaboration aiming to give the students something that wouldn't distract too much from ongoing research," said Weissman. "But they wanted to do more, and that chutzpah led to a paper and a whole new research thrust for the group. This could very well become among the most exciting projects I've ever been involved in."
Weissman stressed the value of the high school students' contribution, even beyond this paper.
"Tens if not hundreds of thousands of human engineering hours went into designing an algorithm that three high schoolers came and kicked its butt," said Weissman. "It's humbling to consider how far we are in our engineering."
Due to the success of this collaboration, Weissman has created a formal summer internship program in his lab for high schoolers. Imagining how an artist or students interested in psychology or neuroscience could contribute to this work, he is particularly keen to bring on students with varied interests and backgrounds.
Lead authors of this paper are Ashutosh Bhown of Palo Alto High School, Soham Mukherjee of Monta Vista High School and Sean Yang of Saint Francis High School. Weissman is also a member of Stanford Bio-X and the Wu Tsai Neurosciences Institute.
This research was funded by the National Science Foundation, the National Institutes of Health, the Stanford Compression Forum and Google.
Excerpted from "Stanford experiment finds humans beat algorithms at image compression", Stanford News, March 25, 2019.