HCAISep 23, 2020

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

arXiv:2009.11195v124 citations
Originality Incremental advance
AI Analysis

This work addresses the need for user-adaptive multimodal referencing in dynamic automotive contexts, but it is incremental as it builds on existing research by focusing on personalization.

The study tackled the problem of referencing outside objects from a moving vehicle by analyzing person-specific pointing and gaze behaviors, finding significant differences based on object location, surroundings, driving mode, and duration.

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.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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