AR Passenger Content via Gaze Detection
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Solution Overview
Problem
Passengers in autonomous vehicles often fail to notice entertainment and points of interest, such as restaurants or shopping centers, during their journey due to their focus on personal electronic devices, leading to a suboptimal transportation experience.
Innovation Solution
A system that uses pose estimation and gaze detection to provide location-based and personalized content to passengers within the vehicle, superimposing information onto the external environment through translucent displays or projectors, enhancing the passenger experience by highlighting nearby objects of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If passengers use personal electronic devices for entertainment, then individual entertainment needs are met, but awareness of nearby attractions and points of interest is reduced
Solution Approach 1:
The patent introduces an intermediary system consisting of cameras, processors, and display devices that mediates between the external environment and the passenger. The system captures images of the external environment, processes them to identify points of interest, and presents them to passengers through displays, thereby providing attraction information without requiring passengers to look away from their devices or the road
Solution Approach 2:
The system creates copies of the external environment through camera imaging and presents selected information (points of interest) to passengers. Instead of requiring passengers to directly observe the external environment, the system captures visual copies and selectively highlights relevant attractions, making information about nearby places available without interfering with personal device usage
2Loss of information
If the system provides comprehensive content about all nearby locations, then passenger information needs are met, but device complexity and information overload increase
Solution Approach 1:
The system applies local quality by treating different regions of the external environment differently based on their significance. Rather than uniformly processing or presenting all visible locations, the system identifies specific points of interest (restaurants, shopping centers, entertainment venues) and selectively presents information about these locations, giving them enhanced visibility and information density while maintaining simplicity for other areas
Solution Approach 2:
The system performs partial action by selectively processing and presenting only certain information about the external environment. Instead of providing comprehensive data about all locations, it focuses on delivering targeted information about identified points of interest, thereby reducing information overload while meeting passenger needs for attraction awareness
3Adaptability or versatility
If the system uses multiple sensors and processing algorithms for pose estimation and gaze detection, then content personalization is improved, but computational requirements and system complexity increase
Solution Approach 1:
The system employs multi-functionality by using camera data for multiple purposes: capturing the external environment for point of interest identification, detecting passenger pose and gaze direction, and providing visual feedback. This universal use of imaging technology reduces the need for separate specialized sensors while achieving sophisticated content personalization based on passenger orientation and attention
Solution Approach 2:
The system implements self-service by using its own imaging resources to fund its personalization capabilities. The same cameras used for environmental capture also provide pose estimation and gaze detection data, eliminating the need for separate sensor systems. The system serves its own information needs through self-contained imaging and processing
Data Source
AI summary
Systems and methods for providing content to passengers within a passenger compartment of a vehicle based on pose estimation and/or gaze detection. The system can obtain sensor data, such as image data, representing a passenger within a vehicle. The system can then analyze the sensor data using pose estimation to determine a pose of the passenger within the vehicle, and analyze the sensor data using gaze detection to determine a point of gaze of the passenger. Based on the pose and the point of gaze, the system can determine a surface within the vehicle for providing content. Additionally, the system can identify the content to provide, wherein the content can include general content or location-based content. After identifying the surface and the content, the system can provide the content to the passenger via the surface. In some examples, providing the content includes augmenting the outside environment with the content.