Video Ad Insertion Points Detection via Shot Boundary Analysis
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Solution Overview
Problem
Manually inserting video advertisements into source videos is a time-consuming and labor-intensive process that does not account for the real-time nature of interactive user browsing and playback of online source videos.
Innovation Solution
A method for determining video advertisement insertion points by parsing a video into shots, computing degrees of discontinuity and attractiveness for each shot boundary, and inserting advertisements at optimized points to maximize viewer impact, using a video insertion engine that includes a shot parser, boundary analyzer, and advertisement embedder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual insertion of video advertisements is used, then advertisement placement can be controlled, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the manual mechanical process of advertisement insertion with an automated computer-based system. The system uses algorithms to automatically identify shot boundaries, compute discontinuity and attractiveness metrics, and determine optimal insertion points without human intervention, thereby resolving the contradiction between automation and time consumption.
2Extent of automation
If manual insertion of video advertisements is used, then placement decisions can be made, but labor intensity increases
Solution Approach 1:
The patent segments the video content analysis into distinct computational components: shot boundary detection, discontinuity computation, attractiveness computation, and insertion point determination. This segmentation allows the complex automated system to be broken down into manageable modular functions, reducing overall system complexity while maintaining automation.
3Reliability
If advertisements are inserted at any point, then insertion can be performed, but viewer impact may be reduced
Solution Approach 1:
The patent introduces quantitative parameters (discontinuity metric and attractiveness metric) to objectively measure shot boundary quality. By transforming the subjective assessment of placement quality into measurable parameters, the system can reliably identify optimal insertion points that maximize viewer impact, resolving the contradiction between placement effectiveness and measurement difficulty.
Data Source
AI summary
Systems and methods for determining insertion points in a first video stream are described. The insertions points being configured for inserting at least one second video into the first video. In accordance with one embodiment, a method for determining the insertion points includes parsing the first video into a plurality of shots. The plurality of shots includes one or more shot boundaries. The method then determines one or more insertion points by balancing a discontinuity metric and an attractiveness metric of each shot boundary.