ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle

Abstract

Over the past decades, the addition of hundreds of sensors to modern vehicles has led to an exponential increase in their capabilities. This allows for novel approaches to interaction with the vehicle that go beyond traditional touch-based and voice command approaches, such as emotion recognition, head rotation, eye gaze, and pointing gestures. Although gaze and pointing gestures have been used before for referencing objects inside and outside vehicles, the multimodal interaction and fusion of these gestures have so far not been extensively studied. We propose a novel learning-based multimodal fusion approach for referencing outside-the-vehicle objects while maintaining a long driving route in a simulated environment. The proposed multimodal approaches outperform single-modality approaches in multiple aspects and conditions. Moreover, we also demonstrate possible ways to exploit behavioral differences between users when completing the referencing task to realize an adaptable personalized system for each driver. We propose a personalization technique based on the transfer-of-learning concept for exceedingly small data sizes to enhance prediction and adapt to individualistic referencing behavior. Our code is publicly available at https://github.com/amr-gomaa/ML-PersRef.

References in corpus (4)

• Scikit-learn: Machine Learning in Python
• Deep Learning: A Critical Appraisal
• Studying Person-Specific Pointing and Gaze Behavior for Multimodal Referencing of Outside Objects from a Moving Vehicle
• You Have a Point There: Object Selection Inside an Automobile Using Gaze, Head Pose and Finger Pointing

Cited by in corpus (5)

• Adaptive User-Centered Multimodal Interaction towards Reliable and Trusted Automotive Interfaces
• What's on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while Driving
• It's all about you: Personalized in-Vehicle Gesture Recognition with a Time-of-Flight Camera
• Looking for a better fit? An Incremental Learning Multimodal Object Referencing Framework adapting to Individual Drivers
• Multimodal Driver Referencing: A Comparison of Pointing to Objects Inside and Outside the Vehicle