Video Information Push Using Statistical Feature Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing methods for pushing information during video playback require complex image processing and high data computation, particularly involving the partitioning of image frames and image recognition technology.
Innovation Solution
A method and system that acquire statistical characteristic information of video frames in real time, using a client to search for index values in a mapping table and send them to a cloud server, which then retrieves corresponding push information from another mapping table, reducing the need for frame partitioning and image recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image recognition technology is used to identify content in video frames, then information push accuracy is improved, but image processing complexity increases
Solution Approach 1:
The patent extracts only the essential statistical characteristics (luminance histogram, average luminance, standard deviation) from video frames, rather than performing full image recognition. This extraction approach maintains information push accuracy by capturing key visual features while dramatically reducing processing complexity.
Solution Approach 2:
The patent introduces statistical characteristic parameters as intermediaries between the video frame and the information push system. These parameters serve as a simplified representation that bridges the gap between visual content and information retrieval, avoiding the need for complex image recognition while maintaining effectiveness.
2Measurement precision
If full image recognition is performed on each video frame, then information retrieval accuracy is improved, but data computation amount increases
Solution Approach 1:
The patent extracts only the essential statistical characteristics (luminance histogram, average luminance, standard deviation) from video frames, rather than performing full image recognition. This extraction approach maintains information push accuracy by capturing key visual features while dramatically reducing processing complexity.
Solution Approach 2:
The patent creates simplified copies of video frame content in the form of statistical characteristic parameters. These parameter copies retain the essential visual information needed for accurate information retrieval while requiring minimal computational resources to process and transmit.
3Loss of information
If video frames are divided into multiple foci for recognition, then information push completeness is improved, but image processing complexity increases
Solution Approach 1:
The patent merges the analysis of entire video frames into single statistical parameters (overall luminance histogram, average luminance, standard deviation). This merging approach maintains information completeness by capturing global visual characteristics while avoiding the complexity of dividing and processing multiple separate regions.
4Quantity of substance
If statistical characteristic information is transmitted instead of full frame data, then network data traffic is reduced, but information representation capability decreases
Solution Approach 1:
The patent extracts only the essential statistical characteristics (luminance histogram, average luminance, standard deviation) from video frames, rather than performing full image recognition. This extraction approach maintains information push accuracy by capturing key visual features while dramatically reducing processing complexity.
Solution Approach 2:
The patent transforms video frame data from pixel-level representation to parameter-level representation (statistical characteristics). This parameter transformation dramatically reduces data transmission requirements while preserving the essential visual information needed for accurate content-based information retrieval.
Data Source
AI summary
A method for pushing information is disclosed by which a client acquires the statistical characteristic information of a current video frame in real time during video playback on the client; the client then searches a first mapping relationship table consisting of mapping relations between the statistical characteristic information and index values that is established by the client for the index value that matches the acquired statistical characteristic information, and sends the index value thus found to a cloud server; the cloud server searches a second mapping relationship table consisting of mapping relations between the index values and push information that is established by the cloud server for the push information that corresponds to the index value; and finally the client receives and plays or displays the push information. There is also provided a system for pushing information.