人群行为分类数据库--Novel Dataset for Fine-grained Abnormal Behavior Understanding in Crowd

Novel Dataset for Fine-grained Abnormal Behavior Understanding in Crowd 数据库：https://github.com/hosseinm/med

本文针对人群行为分类建立了一个数据库，这里有5类：Panic，Fight，Congestion，Obstacle ，Neutral

目前已有的数据库情况：

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2 Proposed Dataset

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The introduced dataset consists of 31 video sequences in total or as about 44,000 normal and abnormal video clips. The videos were recorded as 30 frames per second using a fixed video camera elevated at a height, overlooking individual walkways and the video resolution is 554 * 235. The crowd density in the scene was changeable, ranging from sparse to very crowded.

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3 Proposed Benchmark

这里我们在新数据库上测试了两类算法：

Dense trajectories [25,26](SeeFig. 4)which have shown to be efficient for action recognition are applied as first method on our dataset.

As second benchmark, we use Histogramof OrientedTracklet (HOT) [14, 15,16] descriptor, which is suitable for the task of abnormality detection

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Emotion-Based Crowd Representation for Abnormality Detection 这篇文献主要是在这个数据库基础上加入 人群表情信息来 辅助 人群行为的分类。

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