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Temporal Dynamical Interactions between Multiple Layers of Local Image Features for Event Detection in Video Sequences

机译:视频序列中的事件检测的多层局部图像特征之间的时间动态相互作用

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In this paper an approach for storing and employing local image features in video processing is presented. The approach is based on the usage of memory cells representing local image features and (non-fixed) spatial positions, which are organized in memory layers. By assigning frame-based recall function and learning procedure to the cells, the memory layers establish a content-based auto-associative memory. Thus, they can be applied to solve several event detection tasks, as it is exemplified by dynamic background supression in a traffic scene, and counting of persons halting before a shopping window in an indoor scene. The case studies suggest that information gathered from the cells (like cell history based scoring values) can be used in various manners for video processing tasks circumventing the need for object segmentation and tracking, typical in many conventional background-differencing methods.
机译:本文介绍了一种用于存储和采用视频处理中的本地图像特征的方法。该方法基于表示局部图像特征的存储器单元的使用和(非固定)空间位置,其在存储器层中组织。通过将基于帧的召回功能和学习过程分配给小区,存储器层建立基于内容的自动关联存储器。因此,可以应用它们来解决几个事件检测任务,因为它是交通场景中动态背景繁文的例子,以及在室内场景中的购物窗口之前停止的人数。案例研究表明,从细胞收集的信息(如小区历史的得分值)可以以各种方式使用,以便在许多传统的背景差分方法中典型地避免对对象分割和跟踪的需求的视频处理任务。

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