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Escalator passenger retrograde motion detection method based on deep learning

An escalator and deep learning technology, applied in the field of computer vision, can solve the problems of single judgment method and low judgment accuracy.

Pending Publication Date: 2020-05-12
ZHEJIANG UNIV
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  • Abstract
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Problems solved by technology

However, this method has a single way of judging, and the accuracy of judging complex retrograde situations is not high.

Method used

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  • Escalator passenger retrograde motion detection method based on deep learning
  • Escalator passenger retrograde motion detection method based on deep learning
  • Escalator passenger retrograde motion detection method based on deep learning

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[0066] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, rather than Full examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts all belong to the protection scope of the present invention.

[0067] Such as figure 1 As shown, the escalator passenger retrograde detection method based on deep learning provided by the present invention comprises the following steps:

[0068] Step 1. Obtain image frames from the monitoring video stream of the escalator, and set the detection region (ROI):

[0069] The video stream comes from the monitoring camera of the escalator. The monitoring camer...

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Abstract

The invention discloses an escalator passenger retrograde motion detection method based on deep learning, and the method comprises the steps: 1, obtaining an image frame from a monitoring video streamof an escalator, and setting a detection region (ROI); 2, detecting the head position of the passenger in the ROI specified in the step 1 by using a target detection algorithm; 3, judging the direction of the head detected in the step 2 by using a classifier, and judging whether the passenger possibly has a retrograde phenomenon or not; 4, tracking each possible retrograde target (head) in the step 3 by using a multi-target tracking algorithm to obtain a tracking trajectory; and step 5, analyzing each track in the step 4, and judging whether the passenger has a retrograde motion behavior or not. According to the algorithm, high accuracy and real-time performance can be achieved under the complex condition, the retrograde motion behavior of passengers on the escalator can be effectively judged, and accidents are avoided.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a deep learning-based method for detecting reverse movement of escalator passengers. Background technique [0002] With the rise of smart phones in China, almost everyone has developed the habit of looking at their phones while walking. Therefore, when taking the escalator, the "head-down people" often go to the wrong elevator entrance without paying attention, and have retrograde behavior. If the behavior is not stopped in time, more serious elevator accidents such as falling down often occur after entering the elevator. According to statistics, the proportion of safety accidents caused by retrograde travel is the largest among all safety accidents. Therefore, detecting whether passengers enter the escalator retrogradely and reminding retrograde passengers is a necessary measure to ensure passenger safety. [0003] At present, most elevators are not equipp...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32
CPCG06V40/10G06V20/53G06V10/25Y02B50/00
Inventor 王曰海柳能奚永新唐慧明
Owner ZHEJIANG UNIV
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