Video Music Matching Through Image-Based Soundtrack Recommendation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video editing solutions provide inaccurate soundtrack recommendations with coarse classification granularity, leading to high user effort in finding favorite soundtracks.
Innovation Solution
A method that utilizes image recognition to determine video content features and matches them with a music library, synthesizing candidate soundtracks based on target attribute information and user selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If popular soundtracks are recommended based on usage frequency or growth rate, then the soundtrack selection function is provided to users, but the accuracy of soundtrack recommendation is poor and user search cost is high
Solution Approach 1:
The patent transforms the recommendation basis from simple popularity metrics (usage frequency, growth rate) to a multi-dimensional parameter system including video content features (image recognition results, audio features, text information) and soundtrack features (tempo, genre, mood). This parameter transformation enables accurate matching between video content and suitable soundtracks, resolving the contradiction between recommendation accuracy and selection ease.
Solution Approach 2:
The patent replaces manual soundtrack selection (mechanical user effort) with an automated intelligent recommendation system that uses image recognition, audio analysis, and algorithmic matching. This substitution eliminates the need for users to manually search through categories, directly improving both recommendation accuracy and operational ease.
2Adaptability or versatility
If soundtracks are recommended by coarse classification types (Pop, Rhythm, Fresh, Travel), then users can select from grouped types, but the classification granularity is too coarse and types are not flexible enough
Solution Approach 1:
The patent segments the soundtrack classification system into multiple hierarchical levels and dimensions. Instead of a single coarse classification, the system divides soundtracks into fine-grained categories based on multiple attributes (genre, tempo, mood, instrumentation) that can be independently combined. This segmentation enables both fine granularity and flexible adaptation to different video content types.
Solution Approach 2:
The patent implements a dynamic classification system where soundtrack categories are not fixed but adapt based on the video content being edited. The system dynamically generates or selects appropriate categories and sub-categories based on the detected video features, allowing the classification structure to flexibly adjust to different user needs and content types, thereby achieving both fine granularity and high adaptability.
3Measurement precision
If users manually search and select soundtracks from sub-pages, then users can find their favorite soundtracks, but the operational complexity and time cost are high
Solution Approach 1:
The patent performs preliminary analysis of the video content (image recognition, audio feature extraction, text processing) before the user needs to select a soundtrack. The system pre-processes the video to extract relevant features and pre-generates a customized soundtrack recommendation list based on these features. This preliminary action eliminates the need for users to manually search through categories, directly reducing selection time while maintaining high matching accuracy.
Solution Approach 2:
The patent implements a self-service recommendation system that automatically analyzes video content and generates personalized soundtrack recommendations without requiring user intervention in the search process. The system serves itself by using the video's own features (visual, auditory, textual) to find matching soundtracks, thereby reducing user time investment while achieving accurate matching through automated content-based retrieval.
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
The embodiment of the disclosure provides a method, device, storage medium and program product for video soundtrack. The method includes: obtaining target attribute information of a video material to be soundtracked in a video track of a video editing tool; performing image recognition on the video material to determine an image content feature of the video material; obtaining a candidate soundtrack from a music library based on the target attribute information and the image content feature; and in response to a selection instruction of a user for the candidate soundtrack, synthesizing a target candidate soundtrack selected by the user and the video material. The embodiments of the present disclosure perform soundtrack recommendation based on target attribute information and image content features of the video material, which can improve the accuracy of the soundtrack recommendation, reduce the cost of selecting the soundtrack by the user. Thus, it reduces the operational complexity of selecting the soundtrack as well as editing the video by the user, and facilitates faster and better output of high-quality videos.