首页> 外国专利> LARGE MARGIN HIGH-ORDER DEEP LEARNING WITH AUXILIARY TASKS FOR VIDEO-BASED ANOMALY DETECTION

LARGE MARGIN HIGH-ORDER DEEP LEARNING WITH AUXILIARY TASKS FOR VIDEO-BASED ANOMALY DETECTION

机译:基于辅助异常任务的大型Margin高阶深度学习,用于基于视频的异常检测

摘要

A video camera is provided for video-based anomaly detection that includes at least one imaging sensor configured to capture video sequences in a workplace environment having a plurality of machines therein. The video camera further includes a processor. The processor is configured to generate one or more predictions of an impending anomaly affecting at least one item selected from the group consisting of (i) at least one of the plurality of machines and (ii) at least one operator of the at least one of the plurality of machines, using a Deep High-Order Convolutional Neural Network (DHOCNN)-based model applied to the video sequences. The DHOCNN-based model has a one-class SVM as a loss layer of the model. The processor is further configured to generate a signal for initiating an action to the at least one of the plurality of machines to mitigate expected harm to the at least one item.
机译:提供了一种用于基于视频的异常检测的摄像机,该摄像机包括至少一个成像传感器,该成像传感器被配置为在其中具有多个机器的工作环境中捕获视频序列。该摄像机还包括处理器。所述处理器被配置为生成影响即将发生的异常的一个或多个预测,所述异常影响选自由以下各项组成的组的至少一项:(i)所述多台机器中的至少一台;以及(ii)所述至少一台机器中的至少一名操作员。使用应用于视频序列的基于深度高阶卷积神经网络(DHOCNN)的模型,在多个机器上运行。基于DHOCNN的模型具有一类SVM作为模型的损失层。处理器还被配置为生成信号,该信号用于发起对多个机器中的至少一个的动作,以减轻对至少一个物品的预期伤害。

著录项

  • 公开/公告号US2017286776A1

    专利类型

  • 公开/公告日2017-10-05

    原文格式PDF

  • 申请/专利权人 NEC LABORATORIES AMERICA INC.;

    申请/专利号US201615380308

  • 发明设计人 RENQIANG MIN;DONGJIN SONG;ERIC COSATTO;

    申请日2016-12-15

  • 分类号G06K9;G06K9/66;G06K9/62;G06K9/46;G06N3/08;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-21 13:49:52

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