Multimodal Driver Referencing: A Comparison of Pointing to Objects Inside and Outside the Vehicle

02/15/2022
by   Abdul Rafey Aftab, et al.
2

Advanced in-cabin sensing technologies, especially vision based approaches, have tremendously progressed user interaction inside the vehicle, paving the way for new applications of natural user interaction. Just as humans use multiple modes to communicate with each other, we follow an approach which is characterized by simultaneously using multiple modalities to achieve natural human-machine interaction for a specific task: pointing to or glancing towards objects inside as well as outside the vehicle for deictic references. By tracking the movements of eye-gaze, head and finger, we design a multimodal fusion architecture using a deep neural network to precisely identify the driver's referencing intent. Additionally, we use a speech command as a trigger to separate each referencing event. We observe differences in driver behavior in the two pointing use cases (i.e. for inside and outside objects), especially when analyzing the preciseness of the three modalities eye, head, and finger. We conclude that there is no single modality that is solely optimal for all cases as each modality reveals certain limitations. Fusion of multiple modalities exploits the relevant characteristics of each modality, hence overcoming the case dependent limitations of each individual modality. Ultimately, we propose a method to identity whether the driver's referenced object lies inside or outside the vehicle, based on the predicted pointing direction.

READ FULL TEXT

Authors

page 1

page 4

page 5

page 6

page 10

07/26/2021

Multimodal Fusion Using Deep Learning Applied to Driver's Referencing of Outside-Vehicle Objects

There is a growing interest in more intelligent natural user interaction...
05/30/2021

A Brief Survey on Interactive Automotive UI

Automotive User Interface (AutoUI) is relatively a new discipline in the...
12/24/2020

You Have a Point There: Object Selection Inside an Automobile Using Gaze, Head Pose and Finger Pointing

Sophisticated user interaction in the automotive industry is a fast emer...
11/03/2021

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

Over the past decades, the addition of hundreds of sensors to modern veh...
09/23/2020

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

Hand pointing and eye gaze have been extensively investigated in automot...
04/10/2022

A Comparative Analysis of Decision-Level Fusion for Multimodal Driver Behaviour Understanding

Visual recognition inside the vehicle cabin leads to safer driving and m...
10/13/2020

Jointly Optimizing Sensing Pipelines for Multimodal Mixed Reality Interaction

Natural human interactions for Mixed Reality Applications are overwhelmi...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.