Image-based disaster detection method and apparatus

Patent metadata

Field	Value
Publication number	US-2021225146-A1
Application number	US-202017121287-A
Country	US
Kind code	A1
Filing date	Dec 14, 2020
Priority date	Jan 22, 2020
Publication date	Jul 22, 2021
Grant date	—

Abstract

Disclosed herein are a method and apparatus for detecting a disaster based on images. The apparatus includes an image capture unit for capturing video using at least one camera and controlling the camera based on a camera control signal received from the outside; a disaster detection unit for generating a disaster log based on the video captured using the camera; a disaster analysis unit for calculating a disaster occurrence probability value based on the disaster log and determining whether to enter a camera control mode based on the disaster occurrence probability value; and a disaster alert unit for warning of a disaster based on a disaster alert request signal.

First claim

What is claimed is:

1 . An apparatus for detecting a disaster, comprising:
an image capture unit for capturing video using at least one camera and controlling the camera based on a camera control signal received from an outside; a disaster detection unit for generating a disaster log based on the video captured using the camera; a disaster analysis unit for calculating a disaster occurrence probability value based on the disaster log and determining whether to enter a camera control mode based on the disaster occurrence probability value; and a disaster alert unit for warning of a disaster based on a disaster alert request signal.

2 . The apparatus of claim 1 , wherein:
the camera control signal is capable of including a disaster alert signal and information about a position at which it is suspected that a disaster occurs, and when the camera control signal includes the disaster alert signal and the information about the position at which it is suspected that a disaster occurs, the image capture unit rotates the camera to be directed at the position at which it is suspected that a disaster occurs and controls a lens of the camera so as to zoom in on the corresponding position.

3 . The apparatus of claim 1 , wherein the disaster log includes information about whether a disaster occurs on a time basis and information about a place at which a disaster occurs.

4 . The apparatus of claim 1 , wherein the disaster detection unit detects a disaster based on an image classification method using a convolutional neural network (CNN) model trained by classifying images into general images and disaster images and thereby generates the disaster log.

5 . The apparatus of claim 4 , wherein:
the disaster detection unit performs disaster detection for a video section formed of n images (image sequence) from (t+1*s)-th to (t+n*s)-th frames on a time basis in the video captured using the camera and then performs disaster detection for a video section formed of n images (image sequence) from (t+d+1*s)-th to (t+d+n*s)-th frames, where t denotes a start position of the video, s denotes an interval between frames selected for disaster detection, d denotes an interval between video sections selected for disaster detection, and n denotes the number of images.

6 . The apparatus of claim 1 , wherein the disaster detection unit acquires a video section in which movement of the camera is minimized by calculating the movement of the camera using optical flow or Structure From Motion (SFM) technology and by performing inverse calculation, and generates the disaster log based on the video section.

7 . The apparatus of claim 1 , wherein:
the image capture unit transmits the captured video to a server, and the disaster detection unit receives image data for the captured video from the server and generates the disaster log based on the image data.

8 . An apparatus for detecting a disaster, comprising:
a processor for generating a disaster log based on video captured using at least one camera, calculating a disaster occurrence probability value based on the disaster log, determining whether to enter a camera control mode based on the disaster occurrence probability value, and generating a camera control signal for controlling the camera depending on whether entry into the camera control mode is performed; and memory for storing one or more of the captured video, the camera control signal, and the disaster log.

9 . The apparatus of claim 8 , wherein:
the camera control signal is capable of including a disaster alert signal and information about a position at which it is suspected that a disaster occurs, and when the camera control signal includes the disaster alert signal and the information about the position at which it is suspected that a disaster occurs, the processor rotates the camera to be directed at the position at which it is suspected that a disaster occurs and controls a lens of the camera so as to zoom in on the corresponding position.

10 . The apparatus of claim 8 , wherein the disaster log includes information about whether a disaster occurs on a time basis and information about a place at which a disaster occurs.

11 . The apparatus of claim 8 , wherein the processor detects a disaster based on an image classification method using a convolutional neural network (CNN) model trained by classifying images into general images and disaster images and thereby generates the disaster log.

12 . The apparatus of claim 8 , wherein:
the processor performs disaster detection for a video section formed of n images (image sequence) from (t+1*s)-th to (t+n*s)-th frames on a time basis in the video captured using the camera and then performs disaster detection for a video section formed of n images (image sequence) from (t+d+1*s)-th to (t+d+n*s)-th frames, where t denotes a start position of the video, s denotes an interval between frames selected for disaster detection, d denotes an interval between video sections selected for disaster detection, and n denotes the number of images.

13 . The apparatus of claim 8 , wherein the processor acquires a video section in which movement of the camera is minimized by calculating the movement of the camera using optical flow or Structure From Motion (SFM) technology and by performing inverse calculation, and generates the disaster log based on the video section.

14 . A method for detecting a disaster, comprising:
capturing video using at least one camera; generating a disaster log based on the captured video; calculating a disaster occurrence probability value based on the disaster log; determining whether to enter a camera control mode based on the disaster occurrence probability value; generating a camera control signal for controlling the camera depending on whether entry into the camera control mode is performed; determining whether a disaster occurs based on the disaster occurrence probability value and generating a disaster alert request signal; and warning of the disaster based on the disaster alert request signal,

15 . The method of claim 14 , wherein, When the camera control signal is generated, the camera control signal is capable of including a disaster alert signal and information about a position at which it is suspected that a disaster occurs, and when the camera control signal includes the disaster alert signal and the information about the position at which it is suspected that a disaster occurs, the camera is rotated to be directed at the position at which it is suspected that a disaster occurs, and a lens of the camera is controlled to zoom in on the corresponding position.

16 . The method of claim 14 , wherein the disaster log includes information about whether a disaster occurs on a time basis and information about a place at which a disaster occurs.

17 . The method of claim 14 , wherein generating the disaster log is configured to detect a disaster based on an image classification method using a convolutional neural network (CNN) model trained by classifying images into general images and disaster images and to thereby generate the disaster log.

18 . The method of claim 17 , wherein:
generating the disaster log is configured to perform disaster detection for a video section formed of n images (image sequence) from (t+1*s)-th to (t+n*s)-th frames on a time basis in the video captured using the camera and to then perform disaster detection for a video section formed of n images (image sequence) from (t+d+1*s)-th to (t+d+n*s)-th frames, where t denotes a start position of the v

Assignees

• Electronics & Telecommunications Res Inst

Inventors

• Ghyme Sang-Won
• Kim Hye-Jin
• Oh Seon-Ho
• Kim Geon-Woo
• Park Sang-Wook
• Park So-Hee
• Park Su-Wan
• Lim Kyung-Soo
• Choi Bum-Suk
• Han Seung-Wan
• Han Jong-Wook

Classifications

• G08B17/125 Primary

  by using a video camera to detect fire or smoke · CPC title

• H04N7/181 Primary

  for receiving images from a plurality of remote sources · CPC title

• H04N23/695

  Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects · CPC title

• H04N23/66

  Remote control of cameras or camera parts, e.g. by remote control devices · CPC title

• G06F18/2433

  Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection · CPC title