Event detection using local binary pattern based dynamic textures

Yunqian Ma, P. Císar̆
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引用次数: 34

Abstract

Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. However, these trajectory based descriptors are not working well in the crowd environments like airports, rail stations, because those descriptors assume perfect motion/object segmentation. In this paper, we present an event detection method using dynamic texture descriptor. The dynamic texture descriptor is an extension of the local binary patterns. The image sequences are divided into regions. A flow is formed based on the similarity of the dynamic texture descriptors on the regions. We used real dataset for experiments. The results are promising.
使用基于局部二进制模式的动态纹理进行事件检测
从视频监控摄像机中检测可疑事件已成为近年来的一项重要任务。许多基于轨迹的描述符被开发出来,例如检测在相反方向奔跑或移动的人。然而,这些基于轨迹的描述符在机场、火车站等人群环境中并不能很好地工作,因为这些描述符假设了完美的运动/物体分割。本文提出了一种基于动态纹理描述符的事件检测方法。动态纹理描述符是局部二进制模式的扩展。将图像序列划分为多个区域。基于区域上动态纹理描述符的相似性形成流。我们使用真实数据集进行实验。结果是有希望的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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