基于索引结构的高效运动视频检索

视频片断检索是视频领域的研究热点，为了提高查询效率，利用高维索引结构Vector-Approximation File（VA-File）来组织视频子片段，并采用新的相似度模型和基于限定性滑动窗口的高效视频检索算法进行视频片段检索．提出的子片段的分割算法能够较好地区分运动的细节动作，且相似度模型充分考虑了对应子片段之间的视觉相似性以及时间顺序关系，因此对于运动视频的检索十分有效．实验证明，对于运动视频片段检索不仅具有较高的查询效率，而且能够得到较高的查全率和准确率．

Efficient Sports Video Retrieval Based on Index Structure

Retrieving similar video clips from large video database requires high query efficiency,precision,and recall,and it is a challenging problem in the field of multimedia information retrieval.In this paper,the video stream is segmented into segments by the visual similarity between neighboring frames,and the high-dimensional index structure,the vector-approximation file(VA-file),is adopted to organize the segments.Furthermore,a new similarity measure and query algorithm is proposed,which is based on restricted sliding window to improve the query accuracy.The proposed segmentation algorithm can efficiently represent the details of motion and the new similarity measure can fully take into account the temporal order among video segments.These properties well suit the retrieval of sports videos.Experimental results demonstrate that the proposed video retrieval method is efficient and effective.