基于字典优化的稀疏表示的视频镜头分类  

Video shot classification based on sparse representation of dictionary optimized

作　　者：陈波[1] 詹永照[1] 成科扬[1,2] 

机构地区：[1]江苏大学计算机科学与通信工程学院,江苏镇江212013 [2]南京航空航天大学计算机科学与技术学院,南京212000

出　　处：《计算机应用研究》2012年第6期2375-2378,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(61170126);江苏省自然科学基金资助项目(BK2009199);江苏省省属高校自然科学研究资助项目(11KJD520004);江苏省普通高校研究生科研创新计划资助项目(CXZZ11_0216)

摘　　要：为了克服稀疏表示中冗余字典分类效果不佳的问题,提出了基于字典优化的稀疏表示算法。该算法制定了新的基于稀疏表示的分类判别规则,采用了基于冗余字典内基元类内平均欧式距离最小以及类间平均欧式距离最大的字典优化方法,形成优化字典进行特征稀疏表示。将该算法应用于视频镜头的稀疏表示特征提取与分类,实验结果表明该方法优化后的字典进行视频镜头的特征提取和分类,其识别率得到了明显的提高。In order to overcome the ineffective classification results of the redundant dictionary in the sparse representation-based classifier,this paper presented a sparse representation algorithm based on dictionary optimization.The algorithm developed a new classification discriminate rules based on sparse representation.It optimized the dictionary by the method of minimizing the average of the in-class Euclidean distance and maximized the average of the between-class Euclidean distance,formed the optimized dictionary and presented the features based on sparse representation.And the algorithm was applied on video shot to extract feature and classify based on sparse representation.The experimental results show that the recognition rate of feature extraction and classification on video shot based on the dictionary optimized by this method has been significantly improved.

关 键 词：稀疏表示 字典优化 视频镜头分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]