A Nll-based and Feature Extraction Supported Shot Retrieval Approach

摘要：

　　Nearest Feature Line (NFL) is a convenient and effective way to search in video database,but the Framework does not address the feature extraction for dimension reduction.In this paper,a novel method is proposed for content-based shot retrieval.Karhunen Loeve Transform (KLT) is used to reduce dimensionality of feature spaces.In addition,we present a new take-maximum-from-minima (TMFM) based key frame extraction algorithm,and key-frames extraction is combined with the NFL method to achieve a better performance.Experimental results have shown that our combined method not only achieves superior performance than the NFL and Equal interval (EI),and other classification methods such as Nearest Neighbor (NN) and EI and Nearest Center (NC) and EI but also increases the retrieval speed and reduces the memory significantly without sacrificing the retrieval accuracy.

关键词： Nearest Feature Line Feature Extraction shot retrieval key frame extraction

作者: Zhen Lei Yujun Liu Wenge Zhang Xuelin Liu

作者单位: Academy of Armored Force Engineering Beijing 100072,China Beijing Airspace Control Center Beijing,100720, China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer Application and System Modeling(2012第二届计算机应用与系统建模国际会议)(ICCASM-2012)

会议地点: 沈阳

会议语种:英文

页码: 1072-1075

在线出版日期: 2012-07-27（万方平台首次上网日期，不代表论文的发表时间）