GB202104949D0 - Monocular depth estimation - Google Patents

Monocular depth estimation

Info

Publication number
GB202104949D0
GB202104949D0 GBGB2104949.9A GB202104949A GB202104949D0 GB 202104949 D0 GB202104949 D0 GB 202104949D0 GB 202104949 A GB202104949 A GB 202104949A GB 202104949 D0 GB202104949 D0 GB 202104949D0
Authority
GB
United Kingdom
Prior art keywords
depth estimation
monocular depth
monocular
estimation
depth
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
GBGB2104949.9A
Other versions
GB2605621A (en
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robok Ltd
Original Assignee
Robok 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 Robok Ltd filed Critical Robok Ltd
Priority to GB2104949.9A priority Critical patent/GB2605621A/en
Publication of GB202104949D0 publication Critical patent/GB202104949D0/en
Priority to PCT/GB2022/050881 priority patent/WO2022214821A2/en
Publication of GB2605621A publication Critical patent/GB2605621A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
GB2104949.9A 2021-04-07 2021-04-07 Monocular depth estimation Pending GB2605621A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
GB2104949.9A GB2605621A (en) 2021-04-07 2021-04-07 Monocular depth estimation
PCT/GB2022/050881 WO2022214821A2 (en) 2021-04-07 2022-04-07 Monocular depth estimation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
GB2104949.9A GB2605621A (en) 2021-04-07 2021-04-07 Monocular depth estimation

Publications (2)

Publication Number Publication Date
GB202104949D0 true GB202104949D0 (en) 2021-05-19
GB2605621A GB2605621A (en) 2022-10-12

Family

ID=75883606

Family Applications (1)

Application Number Title Priority Date Filing Date
GB2104949.9A Pending GB2605621A (en) 2021-04-07 2021-04-07 Monocular depth estimation

Country Status (2)

Country Link
GB (1) GB2605621A (en)
WO (1) WO2022214821A2 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111274939B (en) * 2020-01-19 2023-07-14 交信北斗科技有限公司 Automatic extraction method for road pavement pothole damage based on monocular camera

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103337066B (en) 2013-05-27 2016-05-18 清华大学 3D obtains the calibration steps of system
EP3040941B1 (en) 2014-12-29 2017-08-02 Dassault Systèmes Method for calibrating a depth camera
US10154176B1 (en) 2017-05-30 2018-12-11 Intel Corporation Calibrating depth cameras using natural objects with expected shapes
CN109559349B (en) 2017-09-27 2021-11-09 虹软科技股份有限公司 Method and device for calibration
WO2019099684A1 (en) * 2017-11-15 2019-05-23 Google Llc Unsupervised learning of image depth and ego-motion prediction neural networks
US10628968B1 (en) 2018-12-05 2020-04-21 Toyota Research Institute, Inc. Systems and methods of calibrating a depth-IR image offset
CN209541744U (en) 2019-04-26 2019-10-25 昆明理工大学 A kind of caliberating device that photogrammetric post-processing auxiliary scale restores and orients

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
RONNEBERGER ET AL.: "U-Net: Convolutional Networks for Biomedical Image Segmentation", ARXIV: 1505.04597, 2015

Also Published As

Publication number Publication date
GB2605621A (en) 2022-10-12
WO2022214821A2 (en) 2022-10-13
WO2022214821A3 (en) 2022-11-17

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