Invention Grant
- Patent Title: Large margin high-order deep learning with auxiliary tasks for video-based anomaly detection
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Application No.: US15380014Application Date: 2016-12-15
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Publication No.: US10402653B2Publication Date: 2019-09-03
- Inventor: Renqiang Min , Dongjin Song , Eric Cosatto
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: JP
- Assignee: NEC Corporation
- Current Assignee: NEC Corporation
- Current Assignee Address: JP
- Agent Joseph Kolodka
- Main IPC: G06K9/00
- IPC: G06K9/00 ; H04N5/21 ; G06N3/04 ; G06N3/08 ; G06K9/46 ; G06K9/66 ; G06K9/62

Abstract:
A computer-implemented method and system are provided for video-based anomaly detection. The method includes forming, by a processor, a Deep High-Order Convolutional Neural Network (DHOCNN)-based model having a one-class Support Vector Machine (SVM) as a loss layer of the DHOCNN-based model. An objective of the SVM is configured to perform the video-based anomaly detection. The method further includes generating, by the processor, one or more predictions of an impending anomaly based on the high-order deep learning based model applied to an input image. The method also includes initiating, by the processor, an action to a hardware device to mitigate expected harm to at least one item selected from the group consisting of the hardware device, another hardware device related to the hardware device, and a person related to the hardware device.
Public/Granted literature
- US20170289409A1 LARGE MARGIN HIGH-ORDER DEEP LEARNING WITH AUXILIARY TASKS FOR VIDEO-BASED ANOMALY DETECTION Public/Granted day:2017-10-05
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