This thesis examines the integration of mmWave Frequency Modulated Continuous Waveform (FMCW) Radio Detecting And Ranging (RADAR) for context-aware eye tracking in next-generation smart glasses. The innovative use of mmWave FMCW radar technology aims to enhance the functionality and user experience of smart glasses by offering precise eye tracking capabilities and contextual awareness. Apart from eye tracking, mmWave FMCW radar finds applications in augmented and extended reality across various domains including gesture recognition, obstacle detection and mapping, localization and navigation, security and surveillance and healthcare. These radars provide strong capabilities that supplement current technologies in AR and XR, thereby enriching immersion, interaction, and functionality within these advanced fields. The research aims to evaluate the suitability, benefits, and limitations of this radar technology for smart glasses. The thesis begins with a literature review that explores the current state of eye tracking technologies and considers the human eye's response to mmWave radiation. The study then focuses on the system model, explaining the principles of radar and the background theory of the FMCW type. The research methodology includes a sequence of experiments aimed at evaluating the performance of the Infineon BGT60TR13C radar operating at 60 GHz across different deployment scenarios, followed by an analysis of accuracy metrics also using neural networks and machine learning approaches. Experimental results demonstrate the feasibility and advantages of using mmWave FMCW radar in smart glasses, including its robustness to environmental changes and minimal invasiveness. The findings highlight the potential of this approach to revolutionize the design and application of smart glasses, making them more intuitive and responsive to user needs. This work contributes to the fields of wearable technology, signal processing, and human-computer interaction, paving the way for future innovations in smart eyewear.
Questa tesi esamina l'integrazione del rilevamento e misurazione radio (RADAR) a onde millimetriche (mmWave) con modulazione di frequenza a onda continua (FMCW) per il tracciamento oculare contestuale negli smart glass di nuova generazione. L'uso innovativo della tecnologia radar mmWave FMCW mira a migliorare la funzionalità e l'esperienza utente degli smart glasses, offrendo capacità precise di tracciamento oculare e consapevolezza contestuale. Oltre all'eye tracking, i radar FMCW a onde millimetriche trovano applicazione nella realtà aumentata ed estesa in vari ambiti, tra cui il riconoscimento dei gesti, il rilevamento e la mappatura degli ostacoli, la localizzazione e la navigazione, la sicurezza e la sorveglianza e la sanità. Questi radar forniscono forti capacità che integrano le attuali tecnologie di AR e XR, arricchendo così l'immersione, l'interazione e la funzionalità in questi campi avanzati. La ricerca ha lo scopo di valutare l'idoneità, i benefici e le limitazioni di questa tecnologia radar per l'uso negli smart glasses. La tesi comincia con una revisione della letteratura che esplora lo stato attuale delle tecnologie di tracciamento oculare e considera la risposta dell'occhio umano alle radiazioni mmWave. Lo studio si concentra poi sul modello del sistema, spiegando i principi del radar e la teoria alla base della FMCW. La metodologia di ricerca comprende una sequenza di esperimenti volti a valutare le prestazioni del radar Infineon BGT60TR13C operante a 60 GHz in diversi scenari di impiego, seguiti da un'analisi delle metriche di accuratezza utilizzando anche l'approccio alle reti neurali e al machine learning. I risultati sperimentali dimostrano la fattibilità e i vantaggi dell'uso di radar FMCW ad onde millimetriche negli smart glass, in termini di robustezza in diversi scenari unita ad un'invasività minima. I risultati evidenziano il potenziale di questo approccio di smart glass. Questo lavoro contribuisce allo sviluppo delle tecnologie indossabili, l'elaborazione dei segnali e dell'interazione uomo-macchina, aprendo la strada a future innovazioni negli smart glasses.
Exploring mmWave FMCW radar for context-aware eye tracking in next-generation smart glasses
GREPPI, MATTIA
2023/2024
Abstract
This thesis examines the integration of mmWave Frequency Modulated Continuous Waveform (FMCW) Radio Detecting And Ranging (RADAR) for context-aware eye tracking in next-generation smart glasses. The innovative use of mmWave FMCW radar technology aims to enhance the functionality and user experience of smart glasses by offering precise eye tracking capabilities and contextual awareness. Apart from eye tracking, mmWave FMCW radar finds applications in augmented and extended reality across various domains including gesture recognition, obstacle detection and mapping, localization and navigation, security and surveillance and healthcare. These radars provide strong capabilities that supplement current technologies in AR and XR, thereby enriching immersion, interaction, and functionality within these advanced fields. The research aims to evaluate the suitability, benefits, and limitations of this radar technology for smart glasses. The thesis begins with a literature review that explores the current state of eye tracking technologies and considers the human eye's response to mmWave radiation. The study then focuses on the system model, explaining the principles of radar and the background theory of the FMCW type. The research methodology includes a sequence of experiments aimed at evaluating the performance of the Infineon BGT60TR13C radar operating at 60 GHz across different deployment scenarios, followed by an analysis of accuracy metrics also using neural networks and machine learning approaches. Experimental results demonstrate the feasibility and advantages of using mmWave FMCW radar in smart glasses, including its robustness to environmental changes and minimal invasiveness. The findings highlight the potential of this approach to revolutionize the design and application of smart glasses, making them more intuitive and responsive to user needs. This work contributes to the fields of wearable technology, signal processing, and human-computer interaction, paving the way for future innovations in smart eyewear.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/223401