首页> 外文会议>IEEE International Symposium on Multimedia >Enhancing the MST-CSS Representation Using Robust Geometric Features, for Efficient Content Based Video Retrieval (CBVR)
【24h】

Enhancing the MST-CSS Representation Using Robust Geometric Features, for Efficient Content Based Video Retrieval (CBVR)

机译:使用鲁棒的几何特征增强MST-CSS表示,用于基于有效的基于内容的视频检索(CBVR)

获取原文

摘要

Multi-Spectro-Temporal Curvature Scale Space (MST-CSS) had been proposed as a video content descriptor in an earlier work, where the peak and saddle points were used for feature points. But these are inadequate to capture the salient features of the MST-CSS surface, producing poor retrieval results. To overcome these, we propose EMST-CSS (Enhanced MST-CSS) as a better feature representation with an improved matching method for CBVR (Content Based Video Retrieval). Comparative study with the existing MST-CSS representation and two state-of-the-art methods for CBVR shows enhanced performance on one synthetic and two real-world datasets.
机译:在较早的工作中,已经提出了多光谱时间曲率刻度空间(MST-CSS)作为视频内容描述符,其中峰值和鞍点用于特征点。但这些是捕获MST-CSS表面的显着特征,产生差的检索结果。为了克服这些,我们将EMST-CSS(增强的MST-CSS)提出了具有更好的特征表示,具有改进的CBVR匹配方法(基于内容的视频检索)。与现有MST-CSS表示的比较研究和用于CBVR的两个最先进的方法显示了一个合成和两个现实世界数据集的增强性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号