DE102019201702A1 - Modulares inpainting Verfahren - Google Patents

Modulares inpainting Verfahren Download PDF

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Publication number
DE102019201702A1
DE102019201702A1 DE102019201702.9A DE102019201702A DE102019201702A1 DE 102019201702 A1 DE102019201702 A1 DE 102019201702A1 DE 102019201702 A DE102019201702 A DE 102019201702A DE 102019201702 A1 DE102019201702 A1 DE 102019201702A1
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DE
Germany
Prior art keywords
image
areas
faulty
incomplete
area
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
DE102019201702.9A
Other languages
German (de)
English (en)
Inventor
Ekaterina Grünwedel
Charlotte Gloger
Andreas PANAKOS
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.)
Aumovio Autonomous Mobility Germany GmbH
Original Assignee
Conti Temic Microelectronic GmbH
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 Conti Temic Microelectronic GmbH filed Critical Conti Temic Microelectronic GmbH
Priority to DE102019201702.9A priority Critical patent/DE102019201702A1/de
Priority to PCT/DE2020/200008 priority patent/WO2020164671A1/de
Priority to CN202080009784.8A priority patent/CN113330480A/zh
Priority to US17/310,566 priority patent/US11961215B2/en
Priority to JP2021542481A priority patent/JP2022517849A/ja
Priority to EP20707560.7A priority patent/EP3924932A1/de
Publication of DE102019201702A1 publication Critical patent/DE102019201702A1/de
Priority to JP2024002421A priority patent/JP2024041895A/ja
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/77—Retouching; Inpainting; Scratch removal
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R1/00—Optical viewing arrangements; Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles
    • B60R1/20—Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles
    • B60R1/22—Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles for viewing an area outside the vehicle, e.g. the exterior of the vehicle
    • B60R1/28—Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles for viewing an area outside the vehicle, e.g. the exterior of the vehicle with an adjustable field of view
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/20—Image enhancement or restoration using local operators
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/60—Image enhancement or restoration using machine learning, e.g. neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/586—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of parking space
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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 OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06T2207/30264—Parking

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Mechanical Engineering (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Closed-Circuit Television Systems (AREA)
DE102019201702.9A 2019-02-11 2019-02-11 Modulares inpainting Verfahren Pending DE102019201702A1 (de)

Priority Applications (7)

Application Number Priority Date Filing Date Title
DE102019201702.9A DE102019201702A1 (de) 2019-02-11 2019-02-11 Modulares inpainting Verfahren
PCT/DE2020/200008 WO2020164671A1 (de) 2019-02-11 2020-01-30 Modulares inpainting verfahren
CN202080009784.8A CN113330480A (zh) 2019-02-11 2020-01-30 模块化图像修复方法
US17/310,566 US11961215B2 (en) 2019-02-11 2020-01-30 Modular inpainting method
JP2021542481A JP2022517849A (ja) 2019-02-11 2020-01-30 モジュール式画像補間方法
EP20707560.7A EP3924932A1 (de) 2019-02-11 2020-01-30 Modulares inpainting verfahren
JP2024002421A JP2024041895A (ja) 2019-02-11 2024-01-11 モジュール式画像補間方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
DE102019201702.9A DE102019201702A1 (de) 2019-02-11 2019-02-11 Modulares inpainting Verfahren

Publications (1)

Publication Number Publication Date
DE102019201702A1 true DE102019201702A1 (de) 2020-08-13

Family

ID=69723762

Family Applications (1)

Application Number Title Priority Date Filing Date
DE102019201702.9A Pending DE102019201702A1 (de) 2019-02-11 2019-02-11 Modulares inpainting Verfahren

Country Status (6)

Country Link
US (1) US11961215B2 (enExample)
EP (1) EP3924932A1 (enExample)
JP (2) JP2022517849A (enExample)
CN (1) CN113330480A (enExample)
DE (1) DE102019201702A1 (enExample)
WO (1) WO2020164671A1 (enExample)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12165406B2 (en) * 2021-12-20 2024-12-10 Here Global B.V. Method, apparatus, and computer program product for identifying and correcting intersection lane geometry in map data
US12013255B2 (en) 2021-12-20 2024-06-18 Here Global B.V. Method, apparatus, and computer program product for correcting lane geometry in map data
CN115272639B (zh) * 2022-09-19 2022-12-23 武汉天际航信息科技股份有限公司 修复图像中车辆区域的方法、装置和计算机程序产品
CN118351288B (zh) * 2024-04-16 2024-11-22 北京积加科技有限公司 图像区域标记修正方法、装置、设备和计算机可读介质

Citations (4)

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US20140347470A1 (en) * 2013-05-23 2014-11-27 GM Global Technology Operations LLC Enhanced top-down view generation in a front curb viewing system
US20150379422A1 (en) * 2014-06-30 2015-12-31 Hewlett-Packard Development Company, L.P. Dataset Augmentation Based on Occlusion and Inpainting
US20160325680A1 (en) * 2015-05-04 2016-11-10 Kamama, Inc. System and method of vehicle sensor management
US20170120817A1 (en) * 2015-10-30 2017-05-04 Bendix Commercial Vehicle Systems Llc Filling in surround view areas blocked by mirrors or other vehicle parts

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JP2005301517A (ja) 2004-04-08 2005-10-27 Toyota Motor Corp 画像処理装置および画像処理方法
JP2006332785A (ja) * 2005-05-23 2006-12-07 Univ Of Tokyo 画像補完装置及び画像補完方法並びにプログラム
US8971612B2 (en) * 2011-12-15 2015-03-03 Microsoft Corporation Learning image processing tasks from scene reconstructions
CN103310415A (zh) 2013-03-15 2013-09-18 清华大学 基于人脸的图像缺损补绘方法及系统
US10380239B2 (en) 2013-12-03 2019-08-13 Sharethrough Inc. Dynamic native advertisment insertion
US9542609B2 (en) * 2014-02-04 2017-01-10 Xerox Corporation Automatic training of a parked vehicle detector for large deployment
EP3224767A1 (en) 2014-11-26 2017-10-04 Curious Al OY Neural network structure and a method thereto
CN104537663B (zh) 2014-12-26 2018-01-02 广东中科遥感技术有限公司 一种图像抖动的快速校正方法
CN106897655A (zh) * 2015-12-18 2017-06-27 富士通株式会社 停车位的检测装置、方法以及图像处理设备
DE102016220651A1 (de) 2016-10-20 2018-04-26 Conti Temic Microelectronic Gmbh Verfahren und Vorrichtung zur Erzeugung einer Fahrzeugumgebungsansicht bei einem Fahrzeug
US10290085B2 (en) * 2016-12-14 2019-05-14 Adobe Inc. Image hole filling that accounts for global structure and local texture
JP2018107573A (ja) * 2016-12-26 2018-07-05 株式会社東海理化電機製作所 車両用視認装置
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140347470A1 (en) * 2013-05-23 2014-11-27 GM Global Technology Operations LLC Enhanced top-down view generation in a front curb viewing system
US20150379422A1 (en) * 2014-06-30 2015-12-31 Hewlett-Packard Development Company, L.P. Dataset Augmentation Based on Occlusion and Inpainting
US20160325680A1 (en) * 2015-05-04 2016-11-10 Kamama, Inc. System and method of vehicle sensor management
US20170120817A1 (en) * 2015-10-30 2017-05-04 Bendix Commercial Vehicle Systems Llc Filling in surround view areas blocked by mirrors or other vehicle parts

Non-Patent Citations (1)

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Title
KÖHLER, R. [et al.]: Mask-Specific Inpainting with Deep Neural Networks. In: Jiang X., Hornegger J., Koch R. (eds) Pattern Recognition. GCPR 2014. Lecture Notes in Computer Science, vol 8753. Springer, Cham, S. 523-534. *

Also Published As

Publication number Publication date
JP2024041895A (ja) 2024-03-27
JP2022517849A (ja) 2022-03-10
US20220156894A1 (en) 2022-05-19
US11961215B2 (en) 2024-04-16
WO2020164671A1 (de) 2020-08-20
EP3924932A1 (de) 2021-12-22
CN113330480A (zh) 2021-08-31

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Owner name: CONTINENTAL AUTONOMOUS MOBILITY GERMANY GMBH, DE

Free format text: FORMER OWNER: CONTI TEMIC MICROELECTRONIC GMBH, 90411 NUERNBERG, DE

Owner name: AUMOVIO AUTONOMOUS MOBILITY GERMANY GMBH, DE

Free format text: FORMER OWNER: CONTI TEMIC MICROELECTRONIC GMBH, 90411 NUERNBERG, DE

R081 Change of applicant/patentee

Owner name: AUMOVIO AUTONOMOUS MOBILITY GERMANY GMBH, DE

Free format text: FORMER OWNER: CONTINENTAL AUTONOMOUS MOBILITY GERMANY GMBH, 85057 INGOLSTADT, DE

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