JP7078392B2 - 深度センサノイズ - Google Patents

深度センサノイズ Download PDF

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JP7078392B2
JP7078392B2 JP2017248111A JP2017248111A JP7078392B2 JP 7078392 B2 JP7078392 B2 JP 7078392B2 JP 2017248111 A JP2017248111 A JP 2017248111A JP 2017248111 A JP2017248111 A JP 2017248111A JP 7078392 B2 JP7078392 B2 JP 7078392B2
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depth
noise
depth map
depth sensor
noisy
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JP2018109976A (ja
JP2018109976A5 (enExample
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アミーネ アヤリ モハメド
ギテニー ヴィンセント
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Dassault Systemes SE
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04—Interpretation of pictures
    • G01C11/30—Interpretation of pictures by triangulation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/36—Videogrammetry, i.e. electronic processing of video signals from a single source or from different sources to give parallax or range information
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/12—Systems for determining distance or velocity not using reflection or reradiation using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/045—Combinations of networks
    • G06N3/0455—Auto-encoder networks; Encoder-decoder networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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 OR CALCULATING; 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 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • G06T7/85—Stereo camera calibration
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds
    • 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]

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Physics (AREA)
  • General Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • Molecular Biology (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Electromagnetism (AREA)
  • Computer Hardware Design (AREA)
  • Geometry (AREA)
  • Signal Processing (AREA)
  • Image Analysis (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Processing (AREA)
JP2017248111A 2016-12-28 2017-12-25 深度センサノイズ Active JP7078392B2 (ja)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP16306838.0 2016-12-28
EP16306838.0A EP3343502B1 (en) 2016-12-28 2016-12-28 Depth sensor noise

Publications (3)

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JP2018109976A JP2018109976A (ja) 2018-07-12
JP2018109976A5 JP2018109976A5 (enExample) 2021-01-21
JP7078392B2 true JP7078392B2 (ja) 2022-05-31

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US (1) US10586309B2 (enExample)
EP (1) EP3343502B1 (enExample)
JP (1) JP7078392B2 (enExample)
CN (1) CN108253941B (enExample)

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US10387751B2 (en) * 2017-01-12 2019-08-20 Arizona Board Of Regents On Behalf Of Arizona State University Methods, apparatuses, and systems for reconstruction-free image recognition from compressive sensors
US10929987B2 (en) * 2017-08-16 2021-02-23 Nvidia Corporation Learning rigidity of dynamic scenes for three-dimensional scene flow estimation
US10552665B2 (en) 2017-12-12 2020-02-04 Seiko Epson Corporation Methods and systems for training an object detection algorithm using synthetic images
US10453220B1 (en) * 2017-12-29 2019-10-22 Perceive Corporation Machine-trained network for misalignment-insensitive depth perception
US10769437B2 (en) 2018-04-10 2020-09-08 Seiko Epson Corporation Adaptive sampling of training views
US10878285B2 (en) * 2018-04-12 2020-12-29 Seiko Epson Corporation Methods and systems for shape based training for an object detection algorithm
RU2698402C1 (ru) * 2018-08-30 2019-08-26 Самсунг Электроникс Ко., Лтд. Способ обучения сверточной нейронной сети для восстановления изображения и система для формирования карты глубины изображения (варианты)
US10634918B2 (en) 2018-09-06 2020-04-28 Seiko Epson Corporation Internal edge verification
EP3674984B1 (en) * 2018-12-29 2024-05-15 Dassault Systèmes Set of neural networks
US11308652B2 (en) * 2019-02-25 2022-04-19 Apple Inc. Rendering objects to match camera noise
EP3736741B1 (en) 2019-05-06 2025-02-12 Dassault Systèmes Experience learning in virtual world
EP3736740B1 (en) * 2019-05-06 2025-02-12 Dassault Systèmes Experience learning in virtual world
CN110298916B (zh) * 2019-06-21 2022-07-01 湖南大学 一种基于合成深度数据的三维人体重建方法
JP7451946B2 (ja) 2019-11-07 2024-03-19 株式会社アイシン 制御装置
CN111612071B (zh) * 2020-05-21 2024-02-02 北京华睿盛德科技有限公司 一种从曲面零件阴影图生成深度图的深度学习方法
US11238307B1 (en) 2020-09-24 2022-02-01 Eagle Technology, Llc System for performing change detection within a 3D geospatial model based upon semantic change detection using deep learning and related methods
US11747468B2 (en) 2020-09-24 2023-09-05 Eagle Technology, Llc System using a priori terrain height data for interferometric synthetic aperture radar (IFSAR) phase disambiguation and related methods
US11587249B2 (en) 2020-09-24 2023-02-21 Eagle Technology, Llc Artificial intelligence (AI) system and methods for generating estimated height maps from electro-optic imagery
US11302071B1 (en) 2020-09-24 2022-04-12 Eagle Technology, Llc Artificial intelligence (AI) system using height seed initialization for extraction of digital elevation models (DEMs) and related methods
JP7468681B2 (ja) * 2020-10-05 2024-04-16 日本電信電話株式会社 学習方法、学習装置、及びプログラム
CN113204010B (zh) * 2021-03-15 2021-11-02 锋睿领创(珠海)科技有限公司 非视域目标检测方法、装置和存储介质
CN113450295B (zh) * 2021-06-15 2022-11-15 浙江大学 一种基于差分对比学习的深度图合成方法
CN113628190B (zh) * 2021-08-11 2024-03-15 跨维(深圳)智能数字科技有限公司 一种深度图去噪方法、装置、电子设备及介质
JP7727563B2 (ja) * 2022-01-20 2025-08-21 京セラ株式会社 深度情報処理装置、深度分布推定方法、深度分布検出システム及び学習済みモデル生成方法

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Publication number Publication date
EP3343502A1 (en) 2018-07-04
JP2018109976A (ja) 2018-07-12
CN108253941B (zh) 2021-11-12
US10586309B2 (en) 2020-03-10
US20180182071A1 (en) 2018-06-28
EP3343502B1 (en) 2019-02-20
CN108253941A (zh) 2018-07-06

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