视频检索:一种基于Kirsch描述符的精确方法

B. H. Shekar, K. R. Holla, M. Kumari
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引用次数: 3

摘要

本文提出了一种基于Kirsch局部描述符的视频检索模型。在第一阶段,输入视频被分割成镜头并提取关键帧。在下一阶段,从每个关键帧中提取局部描述符,并使用k-means聚类过程将其聚类到k个聚类中。给定一个查询帧,以类似的方式从中提取局部描述符,然后使用k近邻搜索算法与数据库视频的描述符进行比较,找到匹配的关键帧。在TRECVID视频片段上进行了实验,验证了该方法在视频检索应用中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video retrieval: An accurate approach based on Kirsch descriptor
In this paper, a video retrieval model is developed based on Kirsch local descriptor. In the first stage, the input video is segmented into shots and keyframes are extracted. In the next stage, local descriptors are extracted from each keyframe and clustered into k clusters using k-means clustering procedure. Given a query frame, the local descriptors are extracted from it in a similar manner, and then compared with the descriptors of the database video using k-nearest neighbor search algorithm to find the matching keyframe. Experiments have been performed on the TRECVID video segments to demonstrate the performance of the proposed approach for video retrieval applications.
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