13 citations · 22 across the 17 of their papers we have counts for
12 papers · 1 filter
OpenGlass: Ultra-Low-Power On-Device AI Eyewear with Event-based Vision
Pietro Bonazzi, Julian Moosmann, Ahmet Celik +2
Smart eyewear enables unobtrusive, context-aware interaction through multimodal sensors and on-device intelligence, but is severely limited by power, memory, and compute constraint…
Event-Based Vision in Space: Applications, Trends, and Future Directions
Luigi Capogrosso, Pietro Bonazzi, Michele Magno
Earth Observation (EO) is undergoing a significant transformation driven by the deployment of novel sensing technologies. Traditional frame-based optical sensors often struggle wit…
Exploiting In-Sensor Computing for Energy-Efficient Earth Observation
Luigi Capogrosso, Pietro Bonazzi, Loris Hoxhaj +1
The rapid growth of the satellite industry has driven a significant increase in geospatial data acquisition, highlighting a critical bottleneck: the severe disparity between the vo…
FTerViT: Fully Ternary Vision Transformer
Szymon Ruciński, Pietro Bonazzi, Engin Türetken +3
Ternary Vision Transformers offer substantial model compression, however state-of-the-art methods only ternarize the encoder layers, leaving patch embeddings, LayerNorm parameters,…
TinyGLASS: Real-Time Self-Supervised In-Sensor Anomaly Detection
Pietro Bonazzi, Rafael Sutter, Luigi Capogrosso +2
Anomaly detection plays a key role in industrial quality control, where defects must be identified despite the scarcity of labeled faulty samples. Recent self-supervised approaches…
PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devices. We introduce PicoSAM3, a li…
PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Applications
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications like smart glasses and IoT devices. We introduce PicoSAM2, a lightweight (1.3M pa…
Towards Low-Latency Event-based Obstacle Avoidance on a FPGA-Drone
Pietro Bonazzi, Christian Vogt, Michael Jost +3
This work quantitatively evaluates the performance of event-based vision systems (EVS) against conventional RGB-based models for action prediction in collision avoidance on an FPGA…
Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware
Pietro Bonazzi, Sizhen Bian, Giovanni Lippolis +3
This paper introduces a neuromorphic methodology for eye tracking, harnessing pure event data captured by a Dynamic Vision Sensor (DVS) camera. The framework integrates a directly…
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
Julian Moosmann, Pietro Bonazzi, Yawei Li +4
Smart glasses are rapidly gaining advanced functions thanks to cutting-edge computing technologies, especially accelerated hardware architectures, and tiny Artificial Intelligence…
Gaze Estimation on Spresense
Thomas Ruegg, Pietro Bonazzi, Andrea Ronco
Gaze estimation is a valuable technology with numerous applications in fields such as human-computer interaction, virtual reality, and medicine. This report presents the implementa…
TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estimation
Pietro Bonazzi, Thomas Ruegg, Sizhen Bian +2
Intelligent edge vision tasks encounter the critical challenge of ensuring power and latency efficiency due to the typically heavy computational load they impose on edge platforms.…