GB2611408B - Scalable and realistic camera blockage dataset generation - Google Patents

Scalable and realistic camera blockage dataset generation Download PDF

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Publication number
GB2611408B
GB2611408B GB2211259.3A GB202211259A GB2611408B GB 2611408 B GB2611408 B GB 2611408B GB 202211259 A GB202211259 A GB 202211259A GB 2611408 B GB2611408 B GB 2611408B
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United Kingdom
Prior art keywords
scalable
dataset generation
realistic camera
camera blockage
blockage
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Active
Application number
GB2211259.3A
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GB2611408A (en
GB202211259D0 (en
Inventor
Yu Pan
Hong Eng You
Guo Ming Fu James
Yang Jiong
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Motional AD LLC
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Motional AD LLC
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Publication of GB2611408A publication Critical patent/GB2611408A/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/64—Circuits for processing colour signals
    • H04N9/74—Circuits for processing colour signals for obtaining special effects
    • H04N9/75—Chroma key
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/60—Editing figures and text; Combining figures or text
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image
    • G06T3/40—Scaling the whole image or part thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image
    • G06T3/60—Rotation of a whole image or part thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/141—Control of illumination
    • 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
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • 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
    • 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
GB2211259.3A 2021-08-04 2022-08-02 Scalable and realistic camera blockage dataset generation Active GB2611408B (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202163229335P 2021-08-04 2021-08-04
US202163229199P 2021-08-04 2021-08-04

Publications (3)

Publication Number Publication Date
GB202211259D0 GB202211259D0 (en) 2022-09-14
GB2611408A GB2611408A (en) 2023-04-05
GB2611408B true GB2611408B (en) 2024-04-03

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GB2211257.7A Active GB2611167B (en) 2021-08-04 2022-08-02 Training a neural network using a data set with labels of multiple granularities
GB2211259.3A Active GB2611408B (en) 2021-08-04 2022-08-02 Scalable and realistic camera blockage dataset generation

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GB2211257.7A Active GB2611167B (en) 2021-08-04 2022-08-02 Training a neural network using a data set with labels of multiple granularities

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KR (2) KR20230020933A (en)
CN (2) CN115705722A (en)
DE (2) DE102022119217A1 (en)
GB (2) GB2611167B (en)

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030026528A (en) * 2001-09-26 2003-04-03 엘지전자 주식회사 Video telecommunication system
US20140368669A1 (en) * 2012-10-04 2014-12-18 Google Inc. Gpu-accelerated background replacement
US20160034786A1 (en) * 2014-07-29 2016-02-04 Microsoft Corporation Computerized machine learning of interesting video sections
US20190156485A1 (en) * 2017-11-21 2019-05-23 Zoox, Inc. Sensor data segmentation
EP3540691A1 (en) * 2018-03-14 2019-09-18 Volvo Car Corporation Method of segmentation and annotation of images
WO2020031243A1 (en) * 2018-08-06 2020-02-13 株式会社島津製作所 Method for correcting teacher label image, method for preparing learned model, and image analysis device
EP3657379A1 (en) * 2018-11-26 2020-05-27 Connaught Electronics Ltd. A neural network image processing apparatus for detecting soiling of an image capturing device
US20210067676A1 (en) * 2018-02-22 2021-03-04 Sony Corporation Image processing apparatus, image processing method, and program

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10867210B2 (en) * 2018-12-21 2020-12-15 Waymo Llc Neural networks for coarse- and fine-object classifications

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030026528A (en) * 2001-09-26 2003-04-03 엘지전자 주식회사 Video telecommunication system
US20140368669A1 (en) * 2012-10-04 2014-12-18 Google Inc. Gpu-accelerated background replacement
US20160034786A1 (en) * 2014-07-29 2016-02-04 Microsoft Corporation Computerized machine learning of interesting video sections
US20190156485A1 (en) * 2017-11-21 2019-05-23 Zoox, Inc. Sensor data segmentation
US20210067676A1 (en) * 2018-02-22 2021-03-04 Sony Corporation Image processing apparatus, image processing method, and program
EP3540691A1 (en) * 2018-03-14 2019-09-18 Volvo Car Corporation Method of segmentation and annotation of images
WO2020031243A1 (en) * 2018-08-06 2020-02-13 株式会社島津製作所 Method for correcting teacher label image, method for preparing learned model, and image analysis device
EP3657379A1 (en) * 2018-11-26 2020-05-27 Connaught Electronics Ltd. A neural network image processing apparatus for detecting soiling of an image capturing device

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Publication number Publication date
CN115705723A (en) 2023-02-17
DE102022119216A1 (en) 2023-02-09
CN115705722A (en) 2023-02-17
GB2611167A (en) 2023-03-29
GB202211257D0 (en) 2022-09-14
DE102022119217A1 (en) 2023-02-09
KR20230020933A (en) 2023-02-13
GB2611167B (en) 2024-04-03
KR20230020932A (en) 2023-02-13
GB2611408A (en) 2023-04-05
GB202211259D0 (en) 2022-09-14

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