Ad Collateral Detection via Visual Attention Models
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Solution Overview
Problem
Existing methods for detecting advertising collateral in camera images are inefficient, relying on pattern matching and requiring user-driven interface, which limits real-time detection and integration with augmented reality views.
Innovation Solution
A method and apparatus that utilize a biologically inspired algorithm combining visual attention models and edge maps to automatically detect advertising collateral in images, allowing real-time detection and correlation with databases, independent of coordinate systems, and enabling augmented reality enhancements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pattern matching methods are used to detect advertising collateral, then detection accuracy can be achieved, but real-time detection and automation are limited
Solution Approach 1:
The patent replaces traditional pattern matching algorithms with a biologically inspired visual attention model that mimics human visual processing. This substitution enables real-time detection by utilizing edge maps and saliency detection mechanisms that are computationally more efficient than exhaustive pattern matching, while maintaining high detection accuracy for advertising collateral in camera images.
2Ease of operation
If user-driven interface is used for ad collateral detection, then interaction control is provided, but automation and efficiency are reduced
Solution Approach 1:
The system implements automatic detection of advertising collateral without requiring user initiation or interaction. The visual attention model continuously processes camera images, automatically identifies ad collateral elements, and provides results without user-driven interface commands, thereby achieving full automation while maintaining operational simplicity.
3Device complexity
If traditional detection methods are used, then implementation simplicity is maintained, but integration with augmented reality and coordinate independence is limited
Solution Approach 1:
The patent transitions from traditional 2D image coordinate systems to a 3D spatial coordinate system that incorporates depth and spatial orientation information. This dimensional enhancement enables seamless integration with augmented reality applications by providing coordinate-independent detection results that can be accurately mapped to spatial positions in the real world, while maintaining implementation feasibility through the use of edge map-based processing.
Data Source
AI summary
A method including transmitting an image from a camera of an apparatus, where the image includes one or more Ad collateral; and automatically detecting by the apparatus at least one of the Ad collateral in the image. An apparatus including at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to automatically discern at least one Ad collateral in a camera image.