JP7707174B2 - 知覚システムを訓練して確認する方法及びシステム - Google Patents

知覚システムを訓練して確認する方法及びシステム Download PDF

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JP7707174B2
JP7707174B2 JP2022543814A JP2022543814A JP7707174B2 JP 7707174 B2 JP7707174 B2 JP 7707174B2 JP 2022543814 A JP2022543814 A JP 2022543814A JP 2022543814 A JP2022543814 A JP 2022543814A JP 7707174 B2 JP7707174 B2 JP 7707174B2
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ユヴァル ネフマディ
エズラ シャハール ベン
シュムエル マンガン
マーク ワグナー
アンナ コーエン
イツィク アヴィタル
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ヴァヤヴィジョン センシング リミテッド
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    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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    • 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 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
    • G06V10/77—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
    • G06V10/776—Validation; Performance evaluation
    • 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
    • G06V10/77—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
    • G06V10/778—Active pattern-learning, e.g. online learning of image or video features
    • G06V10/7784—Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors
    • G06V10/7792—Active pattern-learning, e.g. online learning of image or video features based on feedback from supervisors the supervisor being an automated module, e.g. "intelligent oracle"
    • 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
    • G06V10/77—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
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/803—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of input or preprocessed data
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    • 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
    • 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

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JP2022543814A 2019-09-22 2020-09-22 知覚システムを訓練して確認する方法及びシステム Active JP7707174B2 (ja)

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US12487564B2 (en) 2024-12-19 2025-12-02 Digital Global Systems, Inc. Systems and methods of sensor data fusion
US12314346B2 (en) 2024-12-19 2025-05-27 Digital Global Systems, Inc. Systems and methods of sensor data fusion
US12479105B2 (en) 2024-12-19 2025-11-25 Digital Global Systems, Inc Systems and methods of sensor data fusion

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018032074A (ja) 2016-08-22 2018-03-01 株式会社リコー 画像処理装置、撮像装置、移動体機器制御システム、画像処理方法、及びプログラム
US20190266418A1 (en) 2018-02-27 2019-08-29 Nvidia Corporation Real-time detection of lanes and boundaries by autonomous vehicles
WO2019178253A1 (en) 2018-03-13 2019-09-19 Magic Leap, Inc. Image-enhanced depth sensing using machine learning

Family Cites Families (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
USRE46930E1 (en) 2007-12-21 2018-07-03 Leddartech Inc. Distance detection method and system
US8908159B2 (en) 2011-05-11 2014-12-09 Leddartech Inc. Multiple-field-of-view scannerless optical rangefinder in high ambient background light
JP5629642B2 (ja) 2011-05-19 2014-11-26 株式会社ソニー・コンピュータエンタテインメント 動画像撮影装置、情報処理システム、情報処理装置、および画像データ処理方法
CA2998175C (en) 2012-03-02 2020-11-10 Leddartech Inc. System and method for multipurpose traffic detection and characterization
US9269012B2 (en) 2013-08-22 2016-02-23 Amazon Technologies, Inc. Multi-tracker object tracking
EP3283843B1 (en) 2015-04-01 2024-01-10 Vayavision Sensing Ltd. Generating 3-dimensional maps of a scene using passive and active measurements
US20170140645A1 (en) * 2015-11-06 2017-05-18 The Board Of Regents Of The University Of Oklahoma Traffic monitoring system
EP4428578A3 (en) * 2017-01-03 2025-03-12 Innoviz Technologies Ltd. Lidar systems and methods for detection and classification of objects
CN110494715B (zh) 2017-02-06 2024-11-05 瓦亚视觉感知有限公司 计算机辅助驾驶
US10445928B2 (en) * 2017-02-11 2019-10-15 Vayavision Ltd. Method and system for generating multidimensional maps of a scene using a plurality of sensors of various types
KR102541559B1 (ko) * 2017-08-04 2023-06-08 삼성전자주식회사 관심 객체를 검출하는 방법 및 장치
US10356341B2 (en) 2017-10-13 2019-07-16 Fyusion, Inc. Skeleton-based effects and background replacement
US11292483B2 (en) 2018-02-28 2022-04-05 VayaVision Sensing, Ltd. Managing a change in a physical property of a vehicle due to an external object
US10628686B2 (en) * 2018-03-12 2020-04-21 Waymo Llc Neural networks for object detection and characterization
WO2019177562A1 (en) * 2018-03-15 2019-09-19 Harman International Industries, Incorporated Vehicle system and method for detecting objects and object distance
WO2019182974A2 (en) * 2018-03-21 2019-09-26 Nvidia Corporation Stereo depth estimation using deep neural networks
CN108875595A (zh) * 2018-05-29 2018-11-23 重庆大学 一种基于深度学习和多层特征融合的驾驶场景目标检测方法
CN109002807A (zh) * 2018-07-27 2018-12-14 重庆大学 一种基于ssd神经网络的驾驶场景车辆检测方法
KR102815456B1 (ko) * 2018-09-12 2025-05-30 삼성전자주식회사 영상 처리를 위한 학습 데이터 생성 방법, 영상 처리 방법, 및 그 장치들
US10460208B1 (en) * 2019-01-02 2019-10-29 Cognata Ltd. System and method for generating large simulation data sets for testing an autonomous driver
CA3125623C (en) 2020-07-21 2023-06-27 Leddartech Inc. Beam-steering device particularly for lidar systems
CA3125716C (en) 2020-07-21 2024-04-09 Leddartech Inc. Systems and methods for wide-angle lidar using non-uniform magnification optics
WO2022016274A1 (en) 2020-07-21 2022-01-27 Leddartech Inc. Beam-steering devices and methods for lidar applications

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018032074A (ja) 2016-08-22 2018-03-01 株式会社リコー 画像処理装置、撮像装置、移動体機器制御システム、画像処理方法、及びプログラム
US20190266418A1 (en) 2018-02-27 2019-08-29 Nvidia Corporation Real-time detection of lanes and boundaries by autonomous vehicles
WO2019178253A1 (en) 2018-03-13 2019-09-19 Magic Leap, Inc. Image-enhanced depth sensing using machine learning

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Eric Tzeng et al.,"Adversarial Discriminative Domain Adaptation",2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),米国,IEEE,2017年07月21日,pp.2962-2971
Fan Zhu et al.,"Boosted Cross-Domain Dictionary Learning for Visual Categorization",IEEE Intelligent Systems,米国,IEEE,2016年03月18日,Vol.31, No.3,pp.6-18
Gledson Melotti et al.,"CNN-LIDAR pedestrian classification: combining range and reflectance data",2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES),米国,IEEE,2018年09月12日,pp.1-6
Wen Li et al.,"Visual Recognition in RGB Images and Videos by Learning from RGB-D Data",IEEE Transactions on Pattern Analysis and Machine Intelligence,米国,IEEE,2017年08月02日,Vol.40, No.8,pp.2030-2036

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EP4031835A4 (en) 2023-10-04
WO2021053680A2 (en) 2021-03-25
CA3155593A1 (en) 2021-03-25
EP4031835A2 (en) 2022-07-27
US12093834B2 (en) 2024-09-17
CN114787880A (zh) 2022-07-22
CA3198976A1 (en) 2021-03-25
KR20220093312A (ko) 2022-07-05
WO2021053680A3 (en) 2021-06-17
US20220335729A1 (en) 2022-10-20
US20240419974A1 (en) 2024-12-19
CA3155593C (en) 2023-07-25
JP2022550487A (ja) 2022-12-01

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