KR20220156470A - 상대적 객체 스케일을 추정하기 위한 머신 학습가능 모델의 훈련 - Google Patents

상대적 객체 스케일을 추정하기 위한 머신 학습가능 모델의 훈련 Download PDF

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KR20220156470A
KR20220156470A KR1020220060783A KR20220060783A KR20220156470A KR 20220156470 A KR20220156470 A KR 20220156470A KR 1020220060783 A KR1020220060783 A KR 1020220060783A KR 20220060783 A KR20220060783 A KR 20220060783A KR 20220156470 A KR20220156470 A KR 20220156470A
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이반 소스노빅
아놀드 스몰더스
콘라드 그로
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로베르트 보쉬 게엠베하
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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    • G05—CONTROLLING; REGULATING
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    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
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    • G06—COMPUTING OR CALCULATING; COUNTING
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    • G06N20/00—Machine learning
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 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
    • G06V10/77—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
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Program-controlled manipulators
    • B25J9/16—Program controls
    • B25J9/1694—Program controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
    • B25J9/1697—Vision controlled systems
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/33—Director till display
    • G05B2219/33034—Online learning, training
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/35—Nc in input of data, input till input file format
    • G05B2219/35074—Display object, recognition of geometric forms
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/20—Control system inputs
    • G05D1/22—Command input arrangements
    • G05D1/221—Remote-control arrangements
    • G05D1/227—Handing over between remote control and on-board control; Handing over between remote control arrangements
    • 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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KR1020220060783A 2021-05-18 2022-05-18 상대적 객체 스케일을 추정하기 위한 머신 학습가능 모델의 훈련 Pending KR20220156470A (ko)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102021205034.4A DE102021205034A1 (de) 2021-05-18 2021-05-18 Trainieren eines maschinenlernfähigen modells zur schätzung des relativen objektmassstabs
DE102021205034.4 2021-05-18

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KR20220156470A true KR20220156470A (ko) 2022-11-25

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US (1) US12125228B2 (https=)
JP (1) JP2022177826A (https=)
KR (1) KR20220156470A (https=)
CN (1) CN115375908A (https=)
DE (1) DE102021205034A1 (https=)

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CN116089428A (zh) * 2023-01-05 2023-05-09 长城汽车股份有限公司 一种比例尺显示方法、系统、电子设备、车辆及存储介质
US12614406B2 (en) * 2023-07-11 2026-04-28 Capital One Services, Llc Systems and methods for applying scale factors to image objects

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US8625902B2 (en) 2010-07-30 2014-01-07 Qualcomm Incorporated Object recognition using incremental feature extraction
DE102018206848A1 (de) * 2018-05-03 2019-11-07 Robert Bosch Gmbh Verfahren und Vorrichtung zum Ermitteln eines Tiefeninformationsbilds aus einem Eingangsbild
JP7003972B2 (ja) * 2019-06-11 2022-01-21 トヨタ自動車株式会社 距離推定装置、距離推定方法及び距離推定用コンピュータプログラム
EP3965009A1 (en) 2020-09-08 2022-03-09 Robert Bosch GmbH Device and method for training a scale-equivariant convolutional neural network

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CN115375908A (zh) 2022-11-22
JP2022177826A (ja) 2022-12-01
US12125228B2 (en) 2024-10-22
US20220375113A1 (en) 2022-11-24

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