Query-Frame Video Selection Using Similarity And Frame Order
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Solution Overview
Problem
When a video is used as a query, it is difficult to improve the accuracy of selecting a video similar to the query.
Innovation Solution
An image selection apparatus and method that selects a video by using query frames with a condition that similar frame images have a high degree of similarity and maintain the same order as the query frames, ensuring at least two query frames satisfy these criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a video is used as a query to search for similar videos, then the search functionality is enabled, but the accuracy of selection is difficult to improve
Solution Approach 1:
The patent segments the query video into multiple query frames (e.g., 10-100 frames) and processes each frame independently to extract features. This segmentation allows the system to compare individual frames against candidate videos rather than treating the entire video as a single unit, thereby improving selection accuracy while managing computational complexity through efficient frame-level processing
Solution Approach 2:
The patent transitions from comparing videos at a high level (entire video sequences) to comparing at a lower dimension (individual frames). By extracting features from multiple frames and aggregating them, the system operates in a multi-dimensional feature space that captures temporal variations and improves the precision of similar video detection
2Measurement precision
If multiple query frames are used to improve selection accuracy, then the accuracy improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary frame selection by extracting and preparing query frames from the query video before the actual similarity comparison. Features are extracted from these pre-selected frames and stored for rapid comparison against candidate videos. This preliminary preparation reduces the computational burden during the main search process, as the system only needs to compare pre-processed frame features rather than processing entire videos in real-time
Solution Approach 2:
The patent uses a partial set of query frames (10-100 frames) rather than processing every possible frame in the query video. This partial action approach provides sufficient representative samples for accurate similarity detection while significantly reducing processing time compared to exhaustive frame-by-frame analysis of the entire query video
3Measurement precision
If frame-level comparison is performed to improve accuracy, then the accuracy improves, but the computational load increases
Solution Approach 1:
The patent extracts key features from query frames (such as visual descriptors, color histograms, or deep learning embeddings) and stores them as compact representations. During the search process, only these extracted features are compared between query frames and candidate video frames, rather than processing the entire image data. This extraction and compression of essential information maintains high matching accuracy while significantly reducing computational requirements
Data Source
AI summary
A query acquisition unit (610) acquires a query video. A query frame selection unit (620) selects a plurality of query frames from among a plurality of first frame images included in the query video. A video selection unit (630) selects a video by using the plurality of query frames. At this time, the video selection unit (630) uses references (1) and (2) below as a condition for selecting the video.Reference (1) A condition that a “similar frame image whose degree of similarity to a query frame satisfies a first reference is present” is satisfied for at least two query frames.Reference (2) When query frames associated with each of at least two similar frame images are arranged in the same order as that of the at least two similar frame images, the arrangement order coincides with an arrangement order of at least two query frames in a query video.