随着数字视频压缩和网络技术的发展,使得视频比以往更容易被访问.在之前已经开发出一些基于内容的视频检索系统,这里我们先了解下之前的那些基于内容的视频检索方法,然后再提出一种新的分类浏览方法,这种方法能提供更有效的改进基于对象属性分析的检索方式,即一种支持高层视觉概念表征的高效视频内容分析和表示方法,另外还有分级视频分类技术,它能弥补低层和高层语义在视觉语义概念上的差别.这种分层视频数据库索引结构使得我们能够访问更大型的数据库资源,高效的数据库索引树结构为整合视频接入提供了很好的途径,支持更强大的视频搜索引擎.本着减少存储设备成本,提高带宽能力,提高压缩技术,数字视频会更容易做到这点.为了帮助用户查找和检索有效的相关信息,并促进更新更好的检索方式,在索引、浏览、过滤方面我们需要提高先进技术来保证搜索和更新庞大的数据库,现在已经拓展到通过色彩、布局、结构来搜索视频、运动和形态特征 [1].%With the development of digital video compression and network technology makes video more accessible than ever before. Prior has developed a number of content-based video retrieval system, where we first understand before those content-based video retrieval method, and then propose a new classification browsing method, this method can provide more effective improvement based on the object efficient video content analysis and representation attribute analysis retrieval methods, namely high-level conceptual representation of a visual support, in addition to scalable video classification techniques, it can make up the difference between the lower and upper semantic visual semantic concept. This layered video database index structure allows us to access a larger database resources, efficient database index tree structure for the integration of video access provides a good way to support a more powerful video search engine. In the storage device to reduce costs, increase bandwidth capacity, improve compression technology, digital video will be easier to do that. In order to help users to find and retrieve information effectively and to promote new and better ways to retrieve, index, view, we need to improve aspects of advanced filtering technology to ensure search and update a large database, now has expanded through the color, layout, structure to search for videos, motion and morphology.
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