一种基于AI的视频剪辑合成方法及系统
By calculating the cross-segment optical flow failure boundary and extracting local structural feature vectors, the constraints of the transition frame are generated, which solves the problem of uncertain reference frame range in multi-segment video editing and synthesis, and achieves a smoother video splicing effect.
CN122053939BActive Publication Date: 2026-07-17CHONGQING MALYA MEDIA CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING MALYA MEDIA CO LTD
- Filing Date
- 2026-04-13
- Publication Date
- 2026-07-17
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Figure CN122053939B_ABST
Abstract
本发明涉及视频数据处理技术领域，具体是一种基于AI的视频剪辑合成方法及系统，包括通过光流方向一致性统计量与幅度变异系数构造光流有效性指数，识别跨片段光流失效边界；以帧间归一化光流幅度的累积值为停止条件，确定边界两侧各片段的有效参考帧范围；以时序近邻分量与运动质量分量构造各参考帧的影响因子；以影响因子构造加权协方差矩阵，经特征值分解自适应选取有效结构特征维度，分别形成两侧片段的投影矩阵；在双侧投影矩阵的联合约束下，以有效参考帧计数为加权系数最小化双侧投影残差，生成过渡帧。本发明解决了视频剪辑拼接过程基于AI生成过渡帧过程的参考帧范围确定、参考帧贡献量化与提取有效特征的问题。
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