WO2022143366A1 - Procédé et appareil de traitement d'image, dispositif électronique, support d'enregistrement, et produit-programme d'ordinateur - Google Patents
Procédé et appareil de traitement d'image, dispositif électronique, support d'enregistrement, et produit-programme d'ordinateur Download PDFInfo
- Publication number
- WO2022143366A1 WO2022143366A1 PCT/CN2021/140683 CN2021140683W WO2022143366A1 WO 2022143366 A1 WO2022143366 A1 WO 2022143366A1 CN 2021140683 W CN2021140683 W CN 2021140683W WO 2022143366 A1 WO2022143366 A1 WO 2022143366A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- image
- map
- segmentation
- predicted
- target
- Prior art date
Links
- 238000004590 computer program Methods 0.000 title claims abstract description 32
- 238000003672 processing method Methods 0.000 title claims abstract description 29
- 238000012545 processing Methods 0.000 claims abstract description 135
- 230000011218 segmentation Effects 0.000 claims abstract description 133
- 238000000034 method Methods 0.000 claims abstract description 85
- 238000003709 image segmentation Methods 0.000 claims abstract description 53
- 230000008569 process Effects 0.000 claims description 39
- 238000012549 training Methods 0.000 claims description 28
- 238000013527 convolutional neural network Methods 0.000 claims description 20
- 238000000605 extraction Methods 0.000 claims description 18
- 230000006870 function Effects 0.000 claims description 16
- 230000015654 memory Effects 0.000 claims description 14
- 238000010586 diagram Methods 0.000 description 14
- 238000004891 communication Methods 0.000 description 9
- 230000014509 gene expression Effects 0.000 description 4
- 238000003491 array Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 238000011176 pooling Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Images
Classifications
-
- 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
- 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
-
- 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
- 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
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- 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
- G06T2207/30244—Camera pose
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Analysis (AREA)
Abstract
Des modes de réalisation de la présente invention concernent un procédé et un appareil de traitement d'image, un dispositif électronique, un support et un produit-programme d'ordinateur. Le procédé consiste à : acquérir une image cible, l'image cible comprenant un objet cible et un objet non cible ; effectuer un traitement de segmentation d'image et un traitement d'estimation de profondeur sur l'image cible pour obtenir une carte de segmentation prédite et une carte de profondeur prédite de l'image cible, respectivement ; déterminer la position de l'objet cible dans la carte de profondeur prédite de l'image cible en fonction d'une carte de segmentation prédite de l'objet cible ; et traiter la carte de profondeur prédite en fonction de la position de l'objet cible dans la carte de profondeur prédite de l'image cible pour obtenir une carte de profondeur prédite de l'objet cible.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110002321.5 | 2021-01-04 | ||
CN202110002321.5A CN113781493A (zh) | 2021-01-04 | 2021-01-04 | 图像处理方法、装置、电子设备、介质及计算机程序产品 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2022143366A1 true WO2022143366A1 (fr) | 2022-07-07 |
Family
ID=78835376
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2021/140683 WO2022143366A1 (fr) | 2021-01-04 | 2021-12-23 | Procédé et appareil de traitement d'image, dispositif électronique, support d'enregistrement, et produit-programme d'ordinateur |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN113781493A (fr) |
WO (1) | WO2022143366A1 (fr) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116029151A (zh) * | 2023-02-09 | 2023-04-28 | 清华大学 | 水流阻力预测方法、训练方法、流量预测方法及装置 |
CN116597213A (zh) * | 2023-05-18 | 2023-08-15 | 北京百度网讯科技有限公司 | 目标检测方法、训练方法、装置、电子设备以及存储介质 |
CN116029151B (zh) * | 2023-02-09 | 2024-05-14 | 清华大学 | 水流阻力预测方法、训练方法、流量预测方法及装置 |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113781493A (zh) * | 2021-01-04 | 2021-12-10 | 北京沃东天骏信息技术有限公司 | 图像处理方法、装置、电子设备、介质及计算机程序产品 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2012074361A1 (fr) * | 2010-12-03 | 2012-06-07 | Mimos Berhad | Procédé de segmentation d'image au moyen d'informations sur l'intensité et la profondeur |
CN109658413A (zh) * | 2018-12-12 | 2019-04-19 | 深圳前海达闼云端智能科技有限公司 | 一种机器人目标物体抓取位置检测的方法 |
CN111311560A (zh) * | 2020-02-10 | 2020-06-19 | 中国铁道科学研究院集团有限公司基础设施检测研究所 | 钢轨扣件状态的检测方法及装置 |
CN111968129A (zh) * | 2020-07-15 | 2020-11-20 | 上海交通大学 | 具有语义感知的即时定位与地图构建系统及方法 |
CN113781493A (zh) * | 2021-01-04 | 2021-12-10 | 北京沃东天骏信息技术有限公司 | 图像处理方法、装置、电子设备、介质及计算机程序产品 |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2014238731A (ja) * | 2013-06-07 | 2014-12-18 | 株式会社ソニー・コンピュータエンタテインメント | 画像処理装置、画像処理システム、および画像処理方法 |
CN104346816B (zh) * | 2014-10-11 | 2017-04-19 | 京东方科技集团股份有限公司 | 一种深度确定方法、装置及电子设备 |
US10019657B2 (en) * | 2015-05-28 | 2018-07-10 | Adobe Systems Incorporated | Joint depth estimation and semantic segmentation from a single image |
CN110969173B (zh) * | 2018-09-28 | 2023-10-24 | 杭州海康威视数字技术股份有限公司 | 目标分类方法及装置 |
US10846870B2 (en) * | 2018-11-29 | 2020-11-24 | Adobe Inc. | Joint training technique for depth map generation |
CN109785345A (zh) * | 2019-01-25 | 2019-05-21 | 中电健康云科技有限公司 | 图像分割方法及装置 |
CN110310229B (zh) * | 2019-06-28 | 2023-04-18 | Oppo广东移动通信有限公司 | 图像处理方法、图像处理装置、终端设备及可读存储介质 |
CN110782468B (zh) * | 2019-10-25 | 2023-04-07 | 北京达佳互联信息技术有限公司 | 图像分割模型的训练方法及装置及图像分割方法及装置 |
-
2021
- 2021-01-04 CN CN202110002321.5A patent/CN113781493A/zh active Pending
- 2021-12-23 WO PCT/CN2021/140683 patent/WO2022143366A1/fr unknown
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2012074361A1 (fr) * | 2010-12-03 | 2012-06-07 | Mimos Berhad | Procédé de segmentation d'image au moyen d'informations sur l'intensité et la profondeur |
CN109658413A (zh) * | 2018-12-12 | 2019-04-19 | 深圳前海达闼云端智能科技有限公司 | 一种机器人目标物体抓取位置检测的方法 |
CN111311560A (zh) * | 2020-02-10 | 2020-06-19 | 中国铁道科学研究院集团有限公司基础设施检测研究所 | 钢轨扣件状态的检测方法及装置 |
CN111968129A (zh) * | 2020-07-15 | 2020-11-20 | 上海交通大学 | 具有语义感知的即时定位与地图构建系统及方法 |
CN113781493A (zh) * | 2021-01-04 | 2021-12-10 | 北京沃东天骏信息技术有限公司 | 图像处理方法、装置、电子设备、介质及计算机程序产品 |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116029151A (zh) * | 2023-02-09 | 2023-04-28 | 清华大学 | 水流阻力预测方法、训练方法、流量预测方法及装置 |
CN116029151B (zh) * | 2023-02-09 | 2024-05-14 | 清华大学 | 水流阻力预测方法、训练方法、流量预测方法及装置 |
CN116597213A (zh) * | 2023-05-18 | 2023-08-15 | 北京百度网讯科技有限公司 | 目标检测方法、训练方法、装置、电子设备以及存储介质 |
Also Published As
Publication number | Publication date |
---|---|
CN113781493A (zh) | 2021-12-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11861829B2 (en) | Deep learning based medical image detection method and related device | |
US11907850B2 (en) | Training image-to-image translation neural networks | |
US11200424B2 (en) | Space-time memory network for locating target object in video content | |
WO2019091464A1 (fr) | Procédé et appareil de détection de cible, procédé d'apprentissage, dispositif électronique et support | |
CN110622177B (zh) | 实例分割 | |
WO2019011249A1 (fr) | Procédé, appareil et dispositif de détermination de pose d'objet dans une image, et support d'informations | |
WO2022143366A1 (fr) | Procédé et appareil de traitement d'image, dispositif électronique, support d'enregistrement, et produit-programme d'ordinateur | |
EP3679521A1 (fr) | Segmentation d'objets par affinage d'antécédents de forme | |
WO2019080747A1 (fr) | Procédé et appareil de suivi de cible, procédé et appareil d'apprentissage de réseau neuronal, support d'informations et dispositif électronique | |
CN108182457B (zh) | 用于生成信息的方法和装置 | |
US20240153240A1 (en) | Image processing method, apparatus, computing device, and medium | |
WO2020062494A1 (fr) | Procédé et appareil de traitement d'image | |
CN113569740B (zh) | 视频识别模型训练方法与装置、视频识别方法与装置 | |
US11544498B2 (en) | Training neural networks using consistency measures | |
WO2020125062A1 (fr) | Procédé de fusion d'image et dispositif associé | |
US20220383630A1 (en) | Training large-scale vision transformer neural networks | |
Li et al. | VNLSTM-PoseNet: A novel deep ConvNet for real-time 6-DOF camera relocalization in urban streets | |
US20230289402A1 (en) | Joint perception model training method, joint perception method, device, and storage medium | |
WO2020101781A1 (fr) | Traitement d'images permettant de localiser de nouveaux objets | |
US10296541B2 (en) | Searching method and apparatus | |
WO2023282847A1 (fr) | Détection d'objets dans une vidéo à l'aide de modèles d'attention | |
JP2022185144A (ja) | 対象検出方法、対象検出モデルのレーニング方法および装置 | |
CN114565768A (zh) | 图像分割方法及装置 | |
CN112508005B (zh) | 用于处理图像的方法、装置、设备以及存储介质 | |
WO2022160897A1 (fr) | Procédé d'estimation de parallaxe binoculaire, procédé d'apprentissage de modèle et dispositif associé |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 21914103 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 20.10.2023) |