JP7211307B2 - 機械学習を使用した距離推定 - Google Patents
機械学習を使用した距離推定 Download PDFInfo
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- JP7211307B2 JP7211307B2 JP2019156732A JP2019156732A JP7211307B2 JP 7211307 B2 JP7211307 B2 JP 7211307B2 JP 2019156732 A JP2019156732 A JP 2019156732A JP 2019156732 A JP2019156732 A JP 2019156732A JP 7211307 B2 JP7211307 B2 JP 7211307B2
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/94—Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
-
- 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
- G06T7/50—Depth or shape recovery
-
- 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
- G06T7/74—Determining position or orientation of objects or cameras using feature-based methods involving reference images or patches
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
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- 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
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- 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
- G06T2207/30256—Lane; Road marking
-
- 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
- G06T2207/30261—Obstacle
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- General Engineering & Computer Science (AREA)
- Image Analysis (AREA)
- Traffic Control Systems (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/116,417 US10867404B2 (en) | 2018-08-29 | 2018-08-29 | Distance estimation using machine learning |
| US16/116,417 | 2018-08-29 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2020047266A JP2020047266A (ja) | 2020-03-26 |
| JP2020047266A5 JP2020047266A5 (https=) | 2022-08-30 |
| JP7211307B2 true JP7211307B2 (ja) | 2023-01-24 |
Family
ID=69641598
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2019156732A Active JP7211307B2 (ja) | 2018-08-29 | 2019-08-29 | 機械学習を使用した距離推定 |
Country Status (2)
| Country | Link |
|---|---|
| US (1) | US10867404B2 (https=) |
| JP (1) | JP7211307B2 (https=) |
Families Citing this family (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7003994B2 (ja) * | 2017-08-08 | 2022-01-21 | ソニーグループ株式会社 | 画像処理装置および方法 |
| EP3782115A1 (en) * | 2018-09-24 | 2021-02-24 | Google LLC | Photo relighting using deep neural networks and confidence learning |
| US10495476B1 (en) | 2018-09-27 | 2019-12-03 | Phiar Technologies, Inc. | Augmented reality navigation systems and methods |
| US11448518B2 (en) * | 2018-09-27 | 2022-09-20 | Phiar Technologies, Inc. | Augmented reality navigational overlay |
| EP3660733B1 (en) * | 2018-11-30 | 2023-06-28 | Tata Consultancy Services Limited | Method and system for information extraction from document images using conversational interface and database querying |
| JP7140209B2 (ja) * | 2018-12-21 | 2022-09-21 | 株式会社ニコン | 検出装置、情報処理装置、検出方法、及び情報処理プログラム |
| JP7336732B2 (ja) * | 2019-03-27 | 2023-09-01 | パナソニックIpマネジメント株式会社 | 無線通信装置、路側機および無線通信方法 |
| US11893482B2 (en) * | 2019-11-14 | 2024-02-06 | Microsoft Technology Licensing, Llc | Image restoration for through-display imaging |
| CN111476731B (zh) * | 2020-04-01 | 2023-06-27 | Oppo广东移动通信有限公司 | 图像矫正方法、装置、存储介质及电子设备 |
| KR102127153B1 (ko) * | 2020-04-09 | 2020-06-26 | 한밭대학교 산학협력단 | 사이클 gan과 세그맨테이션을 사용한 깊이 추정 방법 및 시스템 |
| CN111667420B (zh) * | 2020-05-21 | 2023-10-24 | 维沃移动通信有限公司 | 图像处理方法及装置 |
| CN111651765B (zh) * | 2020-05-27 | 2023-05-02 | 上海交通大学 | 基于生成式对抗网络的程序执行路径生成方法 |
| US12204340B2 (en) | 2020-08-18 | 2025-01-21 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for obstacle detection using a neural network model, depth maps, and segmentation maps |
| JP7662654B2 (ja) * | 2020-09-28 | 2025-04-15 | 富士フイルム株式会社 | 学習装置、方法およびプログラム、画像生成装置、方法およびプログラム、学習済みモデル、仮想画像並びに記録媒体 |
| EP4708200A2 (en) | 2020-09-30 | 2026-03-11 | Google Llc | Enhanced photo relighting based on machine learning models |
| US12394085B2 (en) * | 2020-11-16 | 2025-08-19 | Waymo Llc | Long range distance estimation using reference objects |
| JP7515379B2 (ja) * | 2020-11-24 | 2024-07-12 | 三菱電機株式会社 | 物体検出装置 |
| US12039861B2 (en) | 2021-02-26 | 2024-07-16 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for analyzing the in-lane driving behavior of a road agent external to a vehicle |
| US12134483B2 (en) | 2021-03-10 | 2024-11-05 | The Boeing Company | System and method for automated surface anomaly detection |
| US12530744B2 (en) | 2021-04-28 | 2026-01-20 | Google Llc | Photo relighting and background replacement based on machine learning models |
| US11935254B2 (en) | 2021-06-09 | 2024-03-19 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for predicting depth using style transfer |
| US12014507B2 (en) | 2021-06-10 | 2024-06-18 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for training a prediction system |
| US11900534B2 (en) * | 2021-07-30 | 2024-02-13 | The Boeing Company | Systems and methods for synthetic image generation |
| US11651554B2 (en) * | 2021-07-30 | 2023-05-16 | The Boeing Company | Systems and methods for synthetic image generation |
| US12333828B2 (en) * | 2021-08-04 | 2025-06-17 | Motional Ad Llc | Scalable and realistic camera blockage dataset generation |
| US12548311B2 (en) | 2021-08-04 | 2026-02-10 | Motional Ad Llc | Training a neural network using a data set with labels of multiple granularities |
| CN116205838A (zh) * | 2021-11-30 | 2023-06-02 | 鸿海精密工业股份有限公司 | 异常图像检测方法、系统、终端设备及存储介质 |
| US20230386056A1 (en) * | 2022-05-31 | 2023-11-30 | Qualcomm Incorporated | Systems and techniques for depth estimation |
| DE102022118582B4 (de) * | 2022-07-25 | 2025-07-31 | Carl Zeiss Industrielle Messtechnik Gmbh | Computerimplementiertes Verfahren zum Erzeugen eines korrigierten Bildes mit erweiterter Schärfentiefe, Verfahren, Messgerät und Computerprogrammprodukt |
| US12223563B2 (en) * | 2022-09-27 | 2025-02-11 | Toyota Connected North America, Inc. | Systems and methods for dynamically generating artwork based on vehicle sensor data |
| US20240135510A1 (en) * | 2022-10-06 | 2024-04-25 | Adobe Inc. | Utilizing a generative machine learning model and graphical user interface for creating modified digital images from an infill semantic map |
| US12344374B2 (en) * | 2022-10-13 | 2025-07-01 | Wing Aviation Llc | Obstacle avoidance for aircraft from shadow analysis |
| US20240282117A1 (en) * | 2023-02-22 | 2024-08-22 | Gm Cruise Holdings Llc | Approximately-paired simulation-to-real image translation |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016218999A (ja) | 2015-05-21 | 2016-12-22 | 三菱電機株式会社 | ターゲット環境の画像内に表現されたオブジェクトを検出するように分類器をトレーニングする方法およびシステム |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7113867B1 (en) | 2000-11-26 | 2006-09-26 | Mobileye Technologies Limited | System and method for detecting obstacles to vehicle motion and determining time to contact therewith using sequences of images |
| US8472699B2 (en) | 2006-11-22 | 2013-06-25 | Board Of Trustees Of The Leland Stanford Junior University | Arrangement and method for three-dimensional depth image construction |
| US9979894B1 (en) * | 2014-06-27 | 2018-05-22 | Google Llc | Modifying images with simulated light sources |
| US10068385B2 (en) * | 2015-12-15 | 2018-09-04 | Intel Corporation | Generation of synthetic 3-dimensional object images for recognition systems |
| CN107578436B (zh) | 2017-08-02 | 2020-06-12 | 南京邮电大学 | 一种基于全卷积神经网络fcn的单目图像深度估计方法 |
| US10713569B2 (en) * | 2018-05-31 | 2020-07-14 | Toyota Research Institute, Inc. | System and method for generating improved synthetic images |
-
2018
- 2018-08-29 US US16/116,417 patent/US10867404B2/en not_active Expired - Fee Related
-
2019
- 2019-08-29 JP JP2019156732A patent/JP7211307B2/ja active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016218999A (ja) | 2015-05-21 | 2016-12-22 | 三菱電機株式会社 | ターゲット環境の画像内に表現されたオブジェクトを検出するように分類器をトレーニングする方法およびシステム |
Non-Patent Citations (2)
| Title |
|---|
| Michele Mancini;Gabriele Costante;Paolo Valigi;Thomas A. Ciarfuglia,Fast robust monocular depth estimation for Obstacle Detection with fully convolutional networks,2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),KR,IEEE,2016年10月09日,pp.4296-4303,https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7759632 |
| 高部 篤志,奥行情報と輝度情報の整合性を利用した屋外環境計測データからの移動物体検出,電子情報通信学会技術研究報告 Vol.115 No.457,日本,一般社団法人電子情報通信学会,2016年02月14日,PRMU2015-151, CNR2015-52 (2016-02),P.103-108 |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2020047266A (ja) | 2020-03-26 |
| US20200074674A1 (en) | 2020-03-05 |
| US10867404B2 (en) | 2020-12-15 |
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