In-Vehicle Assistant Interaction Using Real-Time User State Cues
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Solution Overview
Problem
Existing human-machine interaction systems in vehicles lack the ability to effectively convey user information through visual means, limiting the driving/riding experience.
Innovation Solution
An in-vehicle system that captures user images to generate real-time animated visual presentations and physical movements based on facial expressions, hand gestures, and head movements, using machine learning to interpret these cues and control an assistant device's responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional voice commands or text input are used for interaction, then the system is simple to operate, but the user information cannot be effectively conveyed to enhance driving experience
Solution Approach 1:
The system segments user information into multiple modalities: facial expressions, hand gestures, and head movements are captured separately by different sensors and processed independently before being integrated to form a comprehensive user state representation
Solution Approach 2:
The system transitions from one-dimensional text/voice input to multi-dimensional visual interaction by capturing spatial information from cameras, depth data from depth sensors, and gesture positions, adding spatial and temporal dimensions to the interaction paradigm
2Adaptability or versatility
If real-time image processing and animation generation are implemented, then user interaction experience is enhanced, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-processing images to extract user state indicators, pre-generating animated visual presentations based on detected gestures and expressions, and preparing response sequences before actual interaction occurs, reducing real-time computational burden
Solution Approach 2:
The system introduces intermediary components including a dedicated control system that mediates between image capture devices and the assistant system, and an animation generation module that acts as an intermediary between user state detection and visual response output, distributing complexity across multiple specialized subsystems
3Measurement precision
If multiple sensors and processing systems are added to capture facial expressions and gestures, then user state detection accuracy improves, but device complexity increases
Solution Approach 1:
The system merges multiple sensor types (cameras, depth sensors, microphones) and their processing pipelines into an integrated control system that unifiedly handles multi-modal input, combining facial recognition, gesture recognition, and voice processing into a single coordinated framework
Data Source
AI summary
Embodiments of the present disclosure provide a real-time response to a user sitting in a vehicle, such as a driver/passenger. A plurality of images of the user may be captured by a camera disposed in the vehicle. These images may be sent to a control system for processing and outputting a set of user state indicators for characterizing the user's state. Based on the set of user state indicators, an assistant system may programmatically generate one or more animated visual presentations and display the same on a screen of an assistant device as the response to the user's state upon receiving a command sent by the control system. Additionally, the assistant system may also control the physical movement of the assistant device upon receiving a command sent by the control system as the response to the user's head movement.