Dynamic Content Output Device Using Image Difference Detection

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Solution Overview

Problem

Conventional systems for displaying advertisement information based on user attributes fail to prevent boredom and maintain appealing power, as they often display the same content for the same attribute information or rely on random selection, which can be influenced by temporal and seasonal factors.

Innovation Solution

A content output device that acquires images, specifies characteristic elements, compares them to previous images, and outputs content associated with differences in these elements, allowing for dynamic and contextually relevant advertising.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the same advertisement information is displayed for the same attribute information, then consistency is maintained, but viewer boredom increases and appealing power decreases

Engineering Contradiction:

Improveconsistency of content deliveryVSAvoidappealing power of content

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system dynamically selects advertisement content based on changes in characteristic elements between consecutive images. Instead of static content delivery based solely on attribute information, the system introduces temporal dynamics by detecting differences in characteristic elements (such as adding/removal of accessories, clothing changes) and adjusting content selection accordingly. This resolves the contradiction by maintaining reliability through systematic selection while improving appealing power through dynamic adaptation to viewer state changes.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the parameter of content selection from fixed attribute-based matching to dynamic difference-based matching. By introducing a new parameter (difference in characteristic elements between time points) and using it to modulate content selection, the system maintains consistency in its operational logic while improving viewer engagement through adaptive content delivery that responds to actual changes in viewer appearance or state.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If content is selected randomly from multiple items to avoid repetition, then viewer boredom is reduced, but content may be influenced by temporal and seasonal characteristics reducing attractiveness

Engineering Contradiction:

Improvevariety of content presentationVSAvoidattractiveness of content

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system uses feedback from image analysis to guide content selection. By continuously analyzing characteristic elements in images and detecting changes over time, the system creates a closed-loop system where content delivery is informed by actual viewer state. This feedback mechanism ensures variety in content presentation while maintaining attractiveness by selecting content that responds to genuine changes in viewer characteristics rather than arbitrary random selection.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary analysis of characteristic elements and stores them for comparison. By pre-processing and storing characteristic element data from images, the system prepares the foundation for intelligent content selection before the actual content delivery moment arrives. This preliminary action enables the system to make informed content selection decisions based on detected changes, ensuring both variety and attractiveness.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If attribute information is used for content selection, then relevant advertising can be delivered, but the system cannot prevent content that the user is not interested in from being displayed

Engineering Contradiction:

Improverelevance of advertisement to userVSAvoidaccuracy of user interest matching

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system segments the content selection process into two distinct stages: initial selection based on attribute information and subsequent adjustment based on characteristic element changes. This segmentation allows the system to first deliver relevant content based on user attributes, then refine the selection by detecting actual changes in user state (such as adding winter accessories). This two-stage approach improves accuracy by combining broad relevance filtering with specific change-based refinement.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system transitions from static attribute-based content selection to dynamic characteristic-element-based content adjustment. By continuously monitoring changes in characteristic elements between images and using these dynamics to modulate content selection, the system adapts to actual user state changes. This dynamic approach improves accuracy by responding to real-time user behavior rather than relying solely on pre-captured attribute information.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS9530144B2Content output device, content output method, content output program, and recording medium having content output program recorded thereon

Publication Date: 2016.12.27 RAKUTEN GROUP INC

AI summary

An information providing device associates in advance and stores a characteristic element which is a candidate to be specified from an image, with content. Further, the information providing device is configured to specify a difference between characteristic elements by comparing a characteristic element specified from a currently acquired image with a characteristic element specified from an image acquired prior to (in the past) the image, and acquire content associated with the characteristic element related to the difference, and display the content on a display.