Movie Segment Bookmarking for Automated Ad Insertion
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Solution Overview
Problem
Current non-linear video editing systems are complex and difficult to use, requiring high computer skills and offering limited control and flexibility in editing and distributing video content, especially when inserting ads into movies.
Innovation Solution
A method that allows viewers to create deep tags for movie segments, enabling flexible ad placement through a system that processes and transcodes videos, allowing automatic determination of popular segments for ad insertion based on viewer interactions and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If non-linear video editing systems are used, then video content can be edited and distributed, but the systems become complex and difficult to use requiring high computer skills
Solution Approach 1:
The patent introduces an intermediary system that automatically analyzes video content, identifies popular segments, and determines optimal ad placement locations. This intermediary layer handles the complex analysis and decision-making processes, allowing users to simply provide video content and receive professionally edited versions with ads inserted at optimal locations without needing to understand the underlying complexity.
Solution Approach 2:
The system performs self-service by automatically analyzing video content, identifying popular segments through content analysis, and inserting ads without requiring user intervention or complex manual editing. The system serves itself by making intelligent decisions about where to place ads based on automated analysis of video content and viewer engagement patterns.
2Ease of manufacture
If manual ad placement is used, then ad insertion is possible, but it is time consuming and cumbersome
Solution Approach 1:
The system performs preliminary action by pre-analyzing video content to identify popular segments and predetermined ad insertion locations before actual ad placement. This advance analysis allows the system to automatically determine the optimal locations for ad insertion, eliminating the need for time-consuming manual trial and error in finding suitable ad placement points.
Solution Approach 2:
The system changes parameters by using automated content analysis to dynamically determine ad insertion locations based on video content characteristics, viewer engagement metrics, and segment popularity. This parameter-based approach replaces manual time-consuming processes with automated algorithms that quickly analyze and optimize ad placement decisions.
3Productivity
If traditional editing systems are used, then video can be processed, but control and flexibility in editing and distributing video content is limited
Solution Approach 1:
The patent applies segmentation by dividing the video content into distinct segments and identifying popular segments within the video. This segmentation allows for precise control over where ads are inserted, enabling flexible editing and distribution while maintaining high productivity through automated processing of segmented content rather than treating the entire video as a single unit.
Data Source
AI summary
Several ways are provided for a viewer of a movie to create a deep tag, that is, a bookmark for a segment of the movie. The deep tag can be associated with descriptive text and sent to an address provided by the viewer, either an e-mail address or an instant messaging address. Additionally, before the deep tag is created, it can be checked whether the content owner of the movie is known. If known, the content owner's rules, if any, regarding deep tagging are followed. If unknown, a set of registered content owners can be alerted of the presence of new content. When ownership of the new content is established, the already-created deep tags can be updated in accordance with the content owner's rules, if any, regarding deep tagging.