Gaze Estimation on Spresense
Ruegg, Thomas, Bonazzi, Pietro, Ronco, Andrea
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Nov-20-2023
- Country:
- Europe > Switzerland
- North America > United States (0.05)
- Genre:
- Research Report (0.40)
- Technology: