Publikation

Multimodal Driver Interaction using Gesture, Gaze and Speech

Abdul Rafey Aftab

In: ICMI '19: 2019 International Conference on Multimodal Interaction. ACM International Conference on Multimodal Interaction (ICMI-2019) October 14-18 Suyhou China Seiten 487-492 ISBN 78-1-4503-6860-5/19/10 ACM 2019.

Abstrakt

The ever-growing research in computer vision has created new avenues for user interaction. Speech commands and gesture recognition are already being applied in various touch-based inputs. It is, therefore, foreseeable, that the use of multimodal input methods for user interaction is the next phase in development. In this paper, I propose a research plan of novel methods for the use of multimodal inputs for the semantic interpretation of human-computer interaction, specifically applied to a car driver. A fusion methodology has to be designed that adequately makes use of a recognized gesture (specifically finger pointing), eye gaze and head pose for the identification of reference objects, while using the semantics from speech for a natural interactive environment for the driver. The proposed plan includes different techniques based on artificial neural networks for the fusion of the camera-based modalities (gaze, head and gesture). It then combines features extracted from speech with the fusion algorithm to determine the intent of the driver.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence