Video Information Insertion Region Detection
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Solution Overview
Problem
Manual detection of video advertisement insertion spaces in Video-In form is labor-intensive and time-consuming, requiring professional designers and resulting in low accuracy and efficiency.
Innovation Solution
A method and apparatus for automatically detecting information insertion regions in videos by segmenting video frames, identifying objects, clustering candidate regions, and performing maximum rectangle searching to determine optimal insertion areas, thereby reducing manual labor and increasing efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection method is used, then detection accuracy can be maintained through professional judgment, but labor cost and time consumption increase significantly
Solution Approach 1:
The patent replaces the manual mechanical detection process with an automated computer-based system that uses image processing algorithms to identify insertion regions in video frames, eliminating the need for professional designers to manually search through videos while maintaining detection accuracy through structured image analysis
Solution Approach 2:
The system enables self-service detection by automatically analyzing video frames, identifying objects, and determining insertion regions without human intervention, allowing the detection process to serve itself through automated algorithms rather than requiring external professional expertise
2Reliability
If manual detection method is used, then professional judgment can be applied, but productivity and efficiency decrease
Solution Approach 1:
The patent substitutes the manual professional judgment process with an automated system that applies consistent image processing algorithms to identify insertion regions, maintaining reliability through standardized detection criteria while dramatically improving productivity by processing videos automatically without human labor constraints
3Extent of automation
If automated detection is implemented, then labor cost is reduced, but system complexity increases
Solution Approach 1:
The patent segments the video detection process into distinct modules: frame extraction, object identification, region clustering, and insertion point determination. This segmentation reduces system complexity by breaking down the automated detection into manageable, independent processing steps that can be implemented and maintained separately
Data Source
AI summary
A method for detecting an information insertion region is provided. In the method, a video is obtained. The video is segmented to obtain video fragments, each of the video fragments including a subset of image frames in the video. A target frame is obtained in the video fragments. Objects in the target frame are identified and segmented, to obtain labeling information corresponding to the objects. A target object is determined according to the labeling information. Clustering is performed on the target object, to obtain a plurality of candidate to-be-inserted regions. A target candidate to-be-inserted region is determined from the candidate to-be-inserted regions. Further, maximum rectangle searching is performed in the target candidate to-be-inserted region to obtain a target to-be-inserted region in which an image is to be inserted.