Natural interaction with traffic control cameras through multimodal interfaces

TL;DR

This paper presents a multimodal interface using natural language and gestures for traffic control cameras, enhancing interaction speed and naturalness in surveillance scenarios to improve urban safety and security.

Contribution

It introduces a meta user interface leveraging the Put That There paradigm, combining voice and gesture controls via Kinect 2 for efficient traffic surveillance management.

Findings

Effective multimodal interaction with traffic cameras demonstrated

Improved speed and naturalness in user interactions

Enhanced situational awareness in control room scenarios

Abstract

Human-Computer Interfaces have always played a fundamental role in usability and commands' interpretability of the modern software systems. With the explosion of the Artificial Intelligence concept, such interfaces have begun to fill the gap between the user and the system itself, further evolving in Adaptive User Interfaces (AUI). Meta Interfaces are a further step towards the user, and they aim at supporting the human activities in an ambient interactive space; in such a way, the user can control the surrounding space and interact with it. This work aims at proposing a meta user interface that exploits the Put That There paradigm to enable the user to fast interaction by employing natural language and gestures. The application scenario is a video surveillance control room, in which the speed of actions and reactions is fundamental for urban safety and driver and pedestrian security. The interaction is oriented towards three environments: the first is the control room itself, in which the operator can organize the views of the monitors related to the cameras on site by vocal commands and gestures, as well as conveying the audio on the headset or in the speakers of the room. The second one is related to the control of the video, in order to go back and forth to a particular scene showing specific events, or zoom in/out a particular camera; the third allows the operator to send rescue vehicle in a particular street, in case of need. The gestures data are acquired through a Microsoft Kinect 2 which captures pointing and gestures allowing the user to interact multimodally thus increasing the naturalness of the interaction; the related module maps the movement information to a particular instruction, also supported by vocal commands which enable its execution. (cont...)