Video Search System Frame Metadata Analysis
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Solution Overview
Problem
Current mobile devices lack an effective method for identifying video programs, such as movies or TV shows, due to the complexity of processing and searching video content, which requires a more robust search approach compared to still images.
Innovation Solution
A system that captures video files from mobile devices, separates them into individual frames, converts each frame into metadata including pixel, histogram, and audio information, and compares this metadata to pre-indexed metadata in a database to identify matching video files, sending the results back to the mobile device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video files are processed by comparing individual frames and metadata, then video identification accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The video file is divided into multiple individual frames, and each frame is processed separately to extract metadata. This segmentation allows the system to compare specific frames against the database rather than processing the entire video as one unit, improving identification accuracy while managing processing time through selective frame analysis.
Solution Approach 2:
Metadata for video frames is pre-calculated and stored in a database before actual search operations. When a video identification is needed, the system retrieves pre-computed metadata and compares it with the query video's metadata, significantly reducing processing time during actual searches while maintaining high accuracy through comprehensive pre-analysis.
2Adaptability or versatility
If video files are processed by separating into frames and converting to metadata, then search capability is improved, but device complexity increases
Solution Approach 1:
Metadata serves as an intermediary representation between the original video files and the search database. Instead of storing and comparing entire video files, the system converts videos into condensed metadata formats that capture essential visual and audio characteristics, enabling efficient search capability while reducing the complexity of direct video-to-video comparison.
Solution Approach 2:
The system creates metadata copies of video frame information that can be stored and searched without requiring the original video files. These metadata copies contain extracted features such as color histograms, pixel information, and audio characteristics, providing searchable representations that simplify the search process while maintaining identification accuracy.
3Measurement precision
If comprehensive metadata including pixel, histogram, and audio information is extracted, then identification accuracy is improved, but processing complexity and resource usage increase
Solution Approach 1:
The system extracts only the most relevant features from video frames—specifically pixel information, histogram data, and audio characteristics—rather than processing all possible video attributes. This selective extraction maintains identification accuracy by focusing on discriminative features while reducing overall processing complexity and resource consumption compared to analyzing every aspect of the video.
Data Source
AI summary
A system and method identifies a video file in response to a video based search query. A video imaging device in a mobile device captures a video file, and sends the video file to a search engine. A database associated with the search engine stores pre-indexed metadata of pre-indexed frames of video. A video analyzer separates the received video file into individual frames, analyzes the individual frames received from the mobile device by converting the individual frames into metadata, and compares the metadata to the pre-indexed metadata of the pre-indexed frames stored in the database. The video analyzer then sends a message containing information about the identified pre-existing video back to the mobile device based on the comparison of metadata. The metadata of the file and/or the metadata in the database may include one or more of pixel information, histogram information, image recognition information and audio information for each individual frame.