Figure 3: Our BAPose method accurately detects human joints in challenging images that contain multiple people.
of data, expanding the sign distribution analysis to the entire sign language vocabulary. This allowed researchers to identify variations in the distribution of signs between commonly used and more complex signs. These findings were recently published in the journal Cognition. The developments from Bruno Artacho’s doctoral research are a stepping stone towards the automation of complex tasks for sign language analysis, including sign-language recognition, interfaces utilizing gestures as commands, and the analysis of posture and movements for sports or rehabilitation. Furthermore, the waterfall framework developed by Bruno Artacho, was applied to hand pose estimation (HandyPose), vehicle pose estimation (VehiPose) and food segmentation cover article
(GourmetNet) in collaboration with VIP-lab master’s students. Deep learning and computer vision are becoming major drivers for investment in the economy, attracting interest from companies and diverse markets around the world. Rochester, aided by RIT and all the universities in the region, has placed itself in a desirable position to attract talent that will continue revolutionary engineering work, propelling the innovation spirit of the city to be an integral part of the future of artificial intelligence. q Bruno Artacho is a PhD Candidate at RIT. Andreas Savakis is an RIT Professor and Director of the Center for Human-aware Artificial Intelligence." MARCH 2022 The ROCHESTER ENGINEER | 17
