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Professor Jacob O. Wobbrock and two colleagues recently were recognized with the prestigious ACM User Interface Software and Technology () Lasting Impact Award for a paper that became a foundation of gesture-recognition technology.

The highest honor the conference bestows, the ACM UIST Lasting Impact Award annually recognizes a paper that is at least 10 years old for its measurable impact on the field of technical human-computer interaction (HCI).

Published in 2007, the , also known as the $1 Gesture Recognizer, remains a foundational contribution to HCI. Seventeen years later, it is UIST’s fourth most-cited paper of all time with more than 1,100 citations and has been implemented in hundreds of projects. 

Theenables devices to interpret simple stroke gestures, like drawing a triangle or circle, as commands. Designed for rapid prototyping, it simplifies gesture recognition with an intuitive algorithm that identifies gestures quickly and effectively. At just about 100 lines of code, it is easy for developers to implement, making it a highly accessible tool. 

While gesture recognition algorithms predated the $1 Recognizer, it was often complex and difficult to implement. The algorithms used advanced concepts from pattern matching and artificial intelligence, whereas the $1 Recognizer works using just basic geometry and trigonometry, subjects any high schooler could grasp. Wobbrock began exploring gesture recognition as a Ph.D. student in 2003, during an internship with Andrew D. Wilson at Microsoft Research. He faced challenges with gesture recognition when he was assigned to work on the  (later Surface 1.0).  

“I felt that gesture recognition was much harder than it should have to be,” Wobbrock said. “I found some research papers and I saw how this problem had been addressed and all of those approaches were really complicated and didn’t really work that well, especially without providing them with loads of training examples upfront.”

The problem stayed with him, and after becoming a professor at the UW in 2006, Wobbrock revisited the concept. He reached out to Wilson and connected with Yang Li, then a postdoctoral researcher at the UW, to develop a simpler, more intuitive solution. (Li is now a researcher at Google and affiliate faculty at the UW’s Paul G. Allen School of Computer Science & Engineering.) Together, they not only invented the $1 Recognizer, but also built two other predominant recognizers at the time, enabling formal comparisons. Their research showed the $1 Recognizer to be at least as accurate, much faster, and implementable in far fewer lines of code.

The UIST Lasting Impact Award celebrates not just the paper’s achievements but also its influence on other researchers, developers and creative projects worldwide. By turning a challenging concept into an easy-to-use tool, Wobbrock, Wilson and Li not only advanced the field of HCI but also demonstrated the enduring value of making innovation accessible. 

Ironically, although the paper is being recognized for its lasting impact, Wobbrock admitted that it was the lowest ranked paper to be accepted from the pool of submissions to the 2007 UIST conference.

“It almost got rejected,” Wobbrock said. “People were like, this seems too basic, too simple, maybe not cutting-edge enough.”

But its simplicity turned out to be one of the key reasons the $1 Recognizer was implemented in so many different projects.

“The simplicity was its strength, not its weakness,” Wobbrock said. “That just shows at the time, even people didn’t really see that this was going to be that impactful.” 

Over the years, many developers have sent Wobbrock their own implementations of the $1 family recognizers in various programming languages, inspiring researchers to develop follow-ons, which made stroke-gesture recognition easy to add to any user interface. The extended dollar family includes , , , , ,  and . 

“$1 started a whole dollar family,” Wobbrock said. “Even though I know the Impact Award is for the $1 Recognizer paper, it’s really in recognition of the whole dollar family that it started.”

The $1 Recognizer has been featured in various applications, including Wobbrock’s favorite implementations: the video game  and an art project by Zach Lieberman titled “.”

The PC video game Mr. Spiff’s Revenge was developed in 2008 by POW Studios. It was entered into the 2008 Dr. Dobb’s Challenge after two weeks of development and ended up taking home the top prize,”Best Windows Game,” and received a review that highlighted the judges’ enjoyment of the gestures. 

“It came out just one year after we published our paper, showing that there was an immediate uptake,” Wobbrock said. “It’s not very common that academic research papers get found by an industry group, like a game studio. And so that was really fun, that they saw a good use for it.”

by digital artist  uses the  to explore satellite imagery from Google Maps. The user draws a stroke gesture and the project takes the user to a high-resolution satellite image of a part of the world that matches the gesture shape.

“It’s just so clever and educational and creative,” Wobbrock said. “The idea of essentially making motion and then finding that somewhere in the world and seeing that in a satellite image, I think is really clever.”

At this year’s conference in Pittsburgh, Wobbrock reflected on the $1 Recognizer’s impact during his talk, “Making Possible Things Easy.” He emphasized that gesture recognition is an example of how simplifying existing processes can have profound and lasting impact. 

“In technology innovation, we often try to make formerly impossible things possible. But we also need to make difficult things much easier. That is also a valid mission,” Wobbrock said.