Gaze Estimation on Spresense

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PubDate: Aug 2023

Teams: ETH Zurich

Writers: Thomas Ruegg, Pietro Bonazzi, Andrea Ronco

PDF: Gaze Estimation on Spresense


Gaze estimation is a valuable technology with numerous applications in fields such as human-computer interaction, virtual reality, and medicine. This report presents the implementation of a gaze estimation system using the Sony Spresense microcontroller board and explores its performance in latency, MAC/cycle, and power consumption. The report also provides insights into the system’s architecture, including the gaze estimation model used. Additionally, a demonstration of the system is presented, showcasing its functionality and performance. Our lightweight model TinyTrackerS is a mere 169Kb in size, using 85.8k parameters and runs on the Spresense platform at 3 FPS.

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