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cTraj: efficient indexing and searching of sequences containing multiple moving objects

机译：cTraj：高效索引和搜索包含多个运动对象的序列

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摘要

Indexing sequences containing multiple moving objects by all features of these objects captured at every clock tick results in huge index structures due to the large number of extracted features in all sampled instances. Thus, the main problems with current systems that index sequences containing multiple moving objects are: huge storage requirements for index structures, slow search time and low accuracy due to lack of representation of the time-varying features of objects. In this paper, a technique called cTraj to address these problems is proposed. For each object in a sequence, cTraj captures the features at sampled instances. Then, it maps the object's features at each sampled instance from high-dimensional feature space into a point in low-dimensional distance space. The sequence of points of an object in low-dimensional space is considered the time-varying feature trajectory of the object. To reduce storage requirements of an index structure, the sequence of points in each trajectory is represented by a minimum bounding box (MBB). cTraj indexes a sequence by the MBBs of its objects using a spatial access method (SAM), such as an R-tree; thus, greatly reducing storage requirements of the index and speeding up the search time. The cTraj technique does not result in any false dismissal, but the result might contain a few false alarms, which are removed by a two-step refinement process. The experiments show that the proposed cTraj technique produces effective results comparable to those of a sequential method, however much more efficient.
机译：通过在每个时钟滴答中捕获的这些对象的所有特征，对包含多个运动对象的索引序列会导致巨大的索引结构，这是由于所有采样实例中提取的特征数量很多。因此，当前系统对包含多个运动对象的索引序列进行索引的主要问题是：索引结构的存储需求巨大，搜索时间缓慢以及由于缺乏对象随时间变化特征的表示而导致的准确性较低。在本文中，提出了一种称为cTraj的技术来解决这些问题。对于序列中的每个对象，cTraj会在采样实例处捕获特征。然后，它将每个采样实例的对象特征从高维特征空间映射到低维距离空间中的一个点。低维空间中对象的点序列被视为对象的时变特征轨迹。为了减少索引结构的存储要求，每个轨迹中的点序列由最小边界框（MBB）表示。 cTraj使用空间访问方法（SAM），例如R树，通过其对象的MBB对序列进行索引；这样，大大降低了索引的存储需求，加快了搜索时间。 cTraj技术不会导致任何错误消除，但是结果可能包含一些错误警报，这些错误警报可以通过两步优化过程消除。实验表明，提出的cTraj技术可产生与顺序方法相当的有效结果，但是效率更高。

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