Incremental Learning Approach for Events Detection from Large Video Dataset

A. Wali, A. Alimi
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引用次数: 16

Abstract

In this paper, we propose a strategy of multi-SVM incrementallearning system based on Learn++ classifier for detectionof predefined events in the video. This strategy is offlineand fast in the sense that any new class of event can belearned by the system from very few examples. The extractionand synthesis of suitably video events are used for thispurpose. The results showed that the performance of oursystem is improving gradually and progressively as we increasethe number of such learning for each event. We thendemonstrate the usefulness of the toolbox in the context offeature extraction, concepts/events learning and detectionin large collection of video surveillance dataset.
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大型视频数据集事件检测的增量学习方法
本文提出了一种基于Learn++分类器的多支持向量机增量学习系统策略,用于视频中预定义事件的检测。这种策略是离线的,而且速度很快,因为系统可以从很少的例子中学习到任何新的事件类别。为此,采用了适当的视频事件提取和合成方法。结果表明,随着每个事件学习次数的增加,系统的性能逐渐提高。然后,我们展示了工具箱在大量视频监控数据集的特征提取、概念/事件学习和检测方面的有用性。
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