摘要
提出一种视频镜头特征提取方法.针对保局投影变换要预先指定降维后的维数和近邻参数K,根据降维前后的结构误差提出确定最佳降维维数的方法,结合各个数据点邻域的统计特征实现近邻参数K的动态选择.在此基础上,将多个视频镜头的高维特征投影到低维空间获得最佳投影矩阵,新的视频特征根据此投影矩阵进行降维处理.对比实验结果表明,通过保局投影变换提取出来的特征比其它特征更加有利于视频的镜头分割.
A method to extract video feature is introduced. To solve the problems related to the projection dimension and nearest neighbor K in locality preserving projections (LPP), the method to determine the optimal projection dimension based on structure error between dimension reduction before and after is proposed in this papers. The nearest neighbor K is dynamically selected combining with the neighbor statistical character of each data. On the basis of the above an optimal projection matrix of video feature is obtained by using LPP, and then the high dimension feature of new video is reduced to a lower one through the projection matrix. The comparison of experimental results show that the feature based on LPP is more favorable for shot segmentation than the other features.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2010年第3期396-401,共6页
Pattern Recognition and Artificial Intelligence
基金
高等学校博士学科点专项科研基金项目(No.20090162110057)
湖南省自然科学基金项目(No.05JJ30121)
湖南省科技计划项目(No.2009JT3006)
湖南省教育厅项目(No.08B011)
湖南省教育厅教育科学项目(No.09C013)资助
关键词
保局投影(LPP)
特征提取
结构误差
流形学习
Locality Preserving Projections (LPP), Feature Extraction, Structure Error, ManifoldLearning