SG11201909740RA - Method and apparatus for obtaining vehicle loss assessment image, server and terminal device - Google Patents

Method and apparatus for obtaining vehicle loss assessment image, server and terminal device

Info

Publication number
SG11201909740RA
SG11201909740RA SG11201909740RA SG11201909740RA SG 11201909740R A SG11201909740R A SG 11201909740RA SG 11201909740R A SG11201909740R A SG 11201909740RA SG 11201909740R A SG11201909740R A SG 11201909740RA
Authority
SG
Singapore
Prior art keywords
loss assessment
server
images
terminal device
damaged portion
Prior art date
Application number
Inventor
Haitao Zhang
Jinlong Hou
Xin Guo
Yuan Cheng
Jian Wang
Juan Xu
Fan Zhou
Kan Zhang
Original Assignee
Alibaba Group Holding Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Alibaba Group Holding Ltd filed Critical Alibaba Group Holding Ltd
Publication of SG11201909740RA publication Critical patent/SG11201909740RA/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/5838—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • G06Q50/40—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle

Abstract

Embodiments of this application disclose a method, apparatus, server and terminal device for obtaining a vehicle loss assessment image. A client obtains captured video data, and sends the captured video data to a server; the server detects one or more video images in the captured video data to identifies a damaged portion in the one or more video images; the server classifies the one or more video images based on the identified damaged portion to determine one or more candidate image classification sets of the damaged portion; and selects a vehicle loss assessment image from the one or more candidate image classification sets according to a preset screening condition. According to the embodiments of this application, high-quality loss assessment images satisfying loss assessment processing requirements can be automatically and quickly generated, thereby satisfying the loss assessment processing requirements, and improving efficiency of obtaining loss assessment images.
SG11201909740R 2017-04-28 2018-04-27 Method and apparatus for obtaining vehicle loss assessment image, server and terminal device SG11201909740RA (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710294010.4A CN107194323B (en) 2017-04-28 2017-04-28 Vehicle loss assessment image acquisition method and device, server and terminal equipment
PCT/CN2018/084760 WO2018196837A1 (en) 2017-04-28 2018-04-27 Method and apparatus for obtaining vehicle loss assessment image, server and terminal device

Publications (1)

Publication Number Publication Date
SG11201909740RA true SG11201909740RA (en) 2019-11-28

Family

ID=59872897

Family Applications (1)

Application Number Title Priority Date Filing Date
SG11201909740R SG11201909740RA (en) 2017-04-28 2018-04-27 Method and apparatus for obtaining vehicle loss assessment image, server and terminal device

Country Status (9)

Country Link
US (1) US11151384B2 (en)
EP (1) EP3605386A4 (en)
JP (1) JP6905081B2 (en)
KR (1) KR20190139262A (en)
CN (2) CN107194323B (en)
PH (1) PH12019502401A1 (en)
SG (1) SG11201909740RA (en)
TW (1) TW201839666A (en)
WO (1) WO2018196837A1 (en)

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US20200050867A1 (en) 2020-02-13
WO2018196837A1 (en) 2018-11-01
CN107194323B (en) 2020-07-03
JP2020518078A (en) 2020-06-18
CN111914692B (en) 2023-07-14
CN107194323A (en) 2017-09-22
JP6905081B2 (en) 2021-07-21
US11151384B2 (en) 2021-10-19
KR20190139262A (en) 2019-12-17
EP3605386A1 (en) 2020-02-05
CN111914692A (en) 2020-11-10
PH12019502401A1 (en) 2020-12-07
TW201839666A (en) 2018-11-01
EP3605386A4 (en) 2020-04-01

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