Gaze Interaction System for Shop Window Displays
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Solution Overview
Problem
Conventional interactive systems for shop windows and similar displays fail to effectively react to gaze tracking input, especially when multiple users are present, as they rely on users staring at products to select them, which is unnatural, and struggle to determine which user's gaze to respond to.
Innovation Solution
An interactive system that calculates cumulative and average gaze durations to identify the most looked-at products, ranking them for each user, and provides information through display devices, such as slide shows or video clips, while highlighting the most relevant products, allowing for better interaction with single or multiple users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system shows the last looked at product on the display device, then the system reacts to gaze tracking input, but the interaction becomes unnatural as users must stare at products to select them
Solution Approach 1:
The system changes the parameter used for selection from simple gaze presence to cumulative gaze duration. By integrating gaze duration over time and across multiple gazes, the system naturally identifies products of interest without requiring users to maintain continuous stare, thus resolving the contradiction between natural interaction and time loss
Solution Approach 2:
The system introduces an intermediary processing layer that aggregates gaze data from multiple users and time points before determining product selection. This intermediary mechanism (cumulative gaze duration calculation) mediates between individual gaze events and system response, enabling natural multi-user interaction without requiring any single user to stare continuously
2Adaptability or versatility
If the system reacts to single user gaze, then it provides personalized information, but it fails when multiple users are present and cannot determine which user's gaze to respond to
Solution Approach 1:
The system merges gaze data from multiple users by calculating cumulative gaze durations for each product across all users. This combination approach allows the system to handle multiple users simultaneously while preserving individual user preferences through separate tracking, resolving the contradiction between multi-user adaptability and gaze attribution
Solution Approach 2:
The system segments the analysis by first calculating individual user gaze durations for each product, then aggregating these segmented results to determine overall most looked at products. This segmentation preserves user-specific information while enabling multi-user functionality
Data Source
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AI summary
An interactive method and system include at least one detector (210) configured to detect gazes of at least one viewer (250) looking at items (230, 232, 234). A processor (130) is configured to calculate gaze durations, such as cumulative gaze durations per item of the items, identify the most looked at item(s) in accordance with the cumulative gaze durations, and provide information related to the most looked at items. A display device (240) displays the information, a list of the most looked at items, representations of the most looked at items, and/or audio/visual show related to at least one item of the most looked at items. At least one item (290) and/or item representation may be displayed more prominently than others ones of the most looked at items and/or item representations.