Automated Video Preview Generation Using Shot Transition and Speech Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face difficulties in selecting digital content, such as movies and television shows, due to the abundance of available options and the need for user interaction to access content previews, which may not always be available for individual episodes.
Innovation Solution
Automated and semi-automated generation of short video previews using shot transition and human speech detection algorithms, combined with machine learning, to create engaging previews that can be initiated at the home screen, reducing user interaction and providing context without spoilers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional trailers are used to preview content, then users can gauge interest in content, but users must actively interact to access them and they are too long
Solution Approach 1:
The system automatically generates and makes preview clips available before users need them, eliminating the need for users to actively search for or request trailers. The previews are pre-prepared and ready for immediate playback when users browse content.
Solution Approach 2:
The system extracts key moments and essential content from full episodes to create condensed preview clips. By taking out only the most relevant segments and combining them, the system creates concise previews that convey the essence of content without requiring users to watch entire episodes or long trailers.
2Loss of information
If traditional trailers are used to preview content, then users can gauge interest in content, but the trailers are too long
Solution Approach 1:
The system extracts key moments and essential content from full episodes to create condensed preview clips. By taking out only the most relevant segments and combining them, the system creates concise previews that convey the essence of content without requiring users to watch entire episodes or long trailers.
Solution Approach 2:
The system divides content into discrete key moments or scenes and reassembles them into a condensed preview format. This segmentation allows the creation of short, engaging clips that highlight essential plot points without the full duration of original content.
3Productivity
If automated preview generation is implemented, then user interaction is reduced and browsing efficiency improves, but the complexity of the system increases
Solution Approach 1:
The system performs automatic analysis of video content to identify key moments and generate preview clips without human intervention. Machine learning algorithms automatically detect important scenes, extract relevant segments, and assemble previews, eliminating the need for manual trailer creation while improving browsing efficiency.
Solution Approach 2:
The system replaces manual trailer creation processes with automated machine learning-based analysis and generation. Instead of human editors manually selecting and assembling clips, the system uses computational algorithms to automatically identify key moments and create previews, reducing system operational complexity despite increased initial development complexity.
4Ease of operation
If previews are automatically initiated at home screen, then user interaction is minimized, but the risk of playing unwanted content increases
Solution Approach 1:
The system plays only a short preview clip rather than full content, providing just enough information for users to make informed decisions. This partial action approach allows automatic initiation without the harmful effect of users accidentally consuming unwanted full content, as the brief preview can be easily skipped or ignored.
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for systems and methods for automated video preview generation. Example methods may include determining video content, determining a first shot transition, a second shot transition, a third shot transition, and a fourth shot transition in the video content, and determining that human speech is present during the first shot transition and the second shot transition. Example methods may include determining a first timestamp associated with the third shot transition, determining a second timestamp associated with the fourth shot transition, generating a first video preview of the video content, where the first video preview includes a segment of the video content from the first timestamp to the second timestamp, and causing presentation of the first video preview, where the first video preview does not include a segment of the video content between the first shot transition and the second shot transition.