# Studying Person-Specific Pointing and Gaze Behavior for Multimodal Referencing of Outside Objects from a Moving Vehicle

arXiv: https://arxiv.org/abs/2009.11195 · HTML: https://mlsanity.com/paper/2009.11195/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Sep 2020.

## Built on by (most cited first, 8 of 8)

- [ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle](https://mlsanity.com/paper/2111.02327/) (2021)
- [Multimodal Fusion Using Deep Learning Applied to Driver's Referencing of Outside-Vehicle Objects](https://mlsanity.com/paper/2107.12167/) (2021)
- [Adaptive User-Centered Multimodal Interaction towards Reliable and Trusted Automotive Interfaces](https://mlsanity.com/paper/2211.03539/) (2022)
- [What's on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while Driving](https://mlsanity.com/paper/2208.05564/) (2022)
- [It's all about you: Personalized in-Vehicle Gesture Recognition with a Time-of-Flight Camera](https://mlsanity.com/paper/2310.01659/) (2023)
- [Looking for a better fit? An Incremental Learning Multimodal Object Referencing Framework adapting to Individual Drivers](https://mlsanity.com/paper/2401.16123/) (2024)
- [Multimodal Driver Referencing: A Comparison of Pointing to Objects Inside and Outside the Vehicle](https://mlsanity.com/paper/2202.07360/) (2022)
- [Adaptive User-centered Neuro-symbolic Learning for Multimodal Interaction with Autonomous Systems](https://mlsanity.com/paper/2309.05787/) (2023)

## Abstract (arXiv)

Hand pointing and eye gaze have been extensively investigated in automotive applications for object selection and referencing. Despite significant advances, existing outside-the-vehicle referencing methods consider these modalities separately. Moreover, existing multimodal referencing methods focus on a static situation, whereas the situation in a moving vehicle is highly dynamic and subject to safety-critical constraints. In this paper, we investigate the specific characteristics of each modality and the interaction between them when used in the task of referencing outside objects (e.g. buildings) from the vehicle. We furthermore explore person-specific differences in this interaction by analyzing individuals' performance for pointing and gaze patterns, along with their effect on the driving task. Our statistical analysis shows significant differences in individual behaviour based on object's location (i.e. driver's right side vs. left side), object's surroundings, driving mode (i.e. autonomous vs. normal driving) as well as pointing and gaze duration, laying the foundation for a user-adaptive approach.