基于对象的视频相似度检索及其在新闻视频主播镜头检测中的应用

Hua-Tsung Chen, Duan-Yu Chen, Suh-Yin Lee
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引用次数: 6

摘要

视频片段的语义特征提取和视频序列的快速匹配是实现大型视频数据库高效检索的重要手段。提出了一种新的相似度检索机制。考虑连续帧的时空变化,提出了视频序列间的相似性度量方法。为了弥合低层次特征与用户想要捕捉的丰富含义之间的语义差距,对视频镜头进行了压缩域的运动活动高级特征分析和表征。提取的运动活动特征进一步用二维直方图来描述,二维直方图对运动物体的时空变化非常敏感。为了在序列匹配中降低特征向量空间的维数,利用离散余弦变换(DCT)将连续帧的语义特征映射到频域,同时保留区别信息和特征向量之间的欧氏距离。在MPEG-7测试视频流上进行了实验,序列匹配结果表明,少量的DCT变换系数是足够的,从而表明了所提出的视频检索机制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object based video similarity retrieval and its application to detecting anchorperson shots in news video
Semantic feature extraction of video shots and fast video sequence matching are important and required for efficient retrieval in a large video database. A novel mechanism of similarity retrieval is proposed. Similarity measure between video sequences considering the spatio-temporal variation through consecutive frames is presented. For bridging the semantic gap between low-level features and the rich meaning that users desire to capture, video shots are analyzed and characterized by the high-level feature of motion activity in compressed domain. The extracted features of motion activity are further described by the 2D-histogram that is sensitive to the spatio-temporal variation of moving objects. In order to reduce the dimensions of feature vector space in sequence matching, the discrete cosine transform (DCT) is exploited to map semantic features of consecutive frames to the frequency domain while retains the discriminatory information and preserves the Euclidean distance between feature vectors. Experiments are performed on MPEG-7 testing video streams, and the results of sequence matching show that a few DCT transformed coefficients are adequate and thus reveal the effectiveness of the proposed mechanism of video retrieval.
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