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Multiresolution video indexing for subband coded video databases

机译:子带编码视频数据库的多分辨率视频索引

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Abstract: In this paper we present a multiresolution approach for video indexing and feature matching of subband coded video databases. Subband coding refers to a coding technique where the input images are quantized after being decomposed into several narrow spatial frequency bands by filtering and decimation. Five different approaches were tested for scene change detection which is applied only on the lowest subband for computational efficiency. Two kinds of scene changes, abrupt and smoothly accumulated scene changes, mark the beginning of new scene segments. An index for each scene segment is the histogram of two representative frames, which we take to be the first and the last frame of the scene for simplicity. Using the approach of query by example, the index matching algorithm takes a multi-resolution approach by hierarchically comparing histograms at different resolutions. The search algorithm for the match between example query and its target scene segment starts from the coarsest resolution, and moves to the next finer resolution until a single match is obtained or the finest resolution is reached. Experimental results are presented, and the proposed indexing technique appears to be promising for its computational efficiency and its inherent hierarchical search procedure.!18
机译:摘要:在本文中,我们提出了一种用于子带编码视频数据库的视频索引和特征匹配的多分辨率方法。子带编码是指一种编码技术,其中,在通过滤波和抽取将输入图像分解为几个狭窄的空间频带之后,对输入图像进行量化。测试了五种不同的场景更改检测方法,这些方法仅应用于最低子带以提高计算效率。两种场景变化,即突然且平滑累积的场景变化,标志着新场景片段的开始。每个场景片段的索引是两个代表性帧的直方图,为简单起见,我们将其作为场景的第一帧和最后一帧。通过示例查询的方法,索引匹配算法通过分层比较不同分辨率下的直方图,采用了多分辨率方法。用于示例查询与其目标场景片段之间匹配的搜索算法从最粗糙的分辨率开始,然后移至下一个更精细的分辨率,直到获得单个匹配或达到最高分辨率为止。给出了实验结果,并且所提出的索引技术因其计算效率和其固有的分层搜索过程而似乎很有希望!18

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