EP3782075A4 - System zur echtzeit-objektdetektion und -erkennung mit sowohl bild- als auch grössenmerkmalen - Google Patents

System zur echtzeit-objektdetektion und -erkennung mit sowohl bild- als auch grössenmerkmalen Download PDF

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Publication number
EP3782075A4
EP3782075A4 EP19789101.3A EP19789101A EP3782075A4 EP 3782075 A4 EP3782075 A4 EP 3782075A4 EP 19789101 A EP19789101 A EP 19789101A EP 3782075 A4 EP3782075 A4 EP 3782075A4
Authority
EP
European Patent Office
Prior art keywords
recognition
real
image
object detection
time object
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP19789101.3A
Other languages
English (en)
French (fr)
Other versions
EP3782075A1 (de
Inventor
Yang Chen
Deepak Khosla
Ryan M. UHLENBROCK
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
HRL Laboratories LLC
Original Assignee
HRL Laboratories LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by HRL Laboratories LLC filed Critical HRL Laboratories LLC
Publication of EP3782075A1 publication Critical patent/EP3782075A1/de
Publication of EP3782075A4 publication Critical patent/EP3782075A4/de
Pending legal-status Critical Current

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    • 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
    • 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
    • G06F18/24133—Distances to prototypes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06F18/24133—Distances to prototypes
    • G06F18/24143—Distances to neighbourhood prototypes, e.g. restricted Coulomb energy networks [RCEN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/24323—Tree-organised classifiers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/047—Probabilistic or stochastic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/143—Sensing or illuminating at different wavelengths
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/145—Illumination specially adapted for pattern recognition, e.g. using gratings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06V10/50—Extraction of image or video features by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
    • G06V10/507—Summing image-intensity values; Histogram projection analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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; CALCULATING OR 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
    • 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; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/13—Satellite images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Biophysics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Image Analysis (AREA)
EP19789101.3A 2018-04-17 2019-02-14 System zur echtzeit-objektdetektion und -erkennung mit sowohl bild- als auch grössenmerkmalen Pending EP3782075A4 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862659100P 2018-04-17 2018-04-17
PCT/US2019/018119 WO2019203921A1 (en) 2018-04-17 2019-02-14 System for real-time object detection and recognition using both image and size features

Publications (2)

Publication Number Publication Date
EP3782075A1 EP3782075A1 (de) 2021-02-24
EP3782075A4 true EP3782075A4 (de) 2021-12-29

Family

ID=68239189

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19789101.3A Pending EP3782075A4 (de) 2018-04-17 2019-02-14 System zur echtzeit-objektdetektion und -erkennung mit sowohl bild- als auch grössenmerkmalen

Country Status (3)

Country Link
EP (1) EP3782075A4 (de)
CN (1) CN111801689A (de)
WO (1) WO2019203921A1 (de)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
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CN111275054B (zh) * 2020-01-16 2023-10-31 北京迈格威科技有限公司 图像处理方法、装置、电子设备及存储介质
CN112633323B (zh) * 2020-11-26 2024-04-30 成都佳发安泰教育科技股份有限公司 一种用于教室的姿态检测方法和系统
CN112560726B (zh) * 2020-12-22 2023-08-29 阿波罗智联(北京)科技有限公司 目标检测置信度确定方法、路侧设备及云控平台

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US9613273B2 (en) * 2015-05-19 2017-04-04 Toyota Motor Engineering & Manufacturing North America, Inc. Apparatus and method for object tracking
US9582895B2 (en) * 2015-05-22 2017-02-28 International Business Machines Corporation Real-time object analysis with occlusion handling
CN105760858A (zh) * 2016-03-21 2016-07-13 东南大学 一种基于类Haar中间层滤波特征的行人检测方法及装置
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WO2017192629A1 (en) * 2016-05-02 2017-11-09 The Regents Of The University Of California System and method for estimating perfusion parameters using medical imaging
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CN107092883A (zh) * 2017-04-20 2017-08-25 上海极链网络科技有限公司 物体识别追踪方法
CN107273832B (zh) * 2017-06-06 2020-09-22 青海省交通科学研究院 基于积分通道特征与卷积神经网络的车牌识别方法及系统
CN107679525B (zh) * 2017-11-01 2022-11-29 腾讯科技（深圳）有限公司 图像分类方法、装置及计算机可读存储介质

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Title
DONG PEILEI ET AL: "Mask-streaming CNN for pedestrian detection", 2017 IEEE VISUAL COMMUNICATIONS AND IMAGE PROCESSING (VCIP), IEEE, 10 December 2017 (2017-12-10), pages 1 - 4, XP033325734, DOI: 10.1109/VCIP.2017.8305054 *
LU KEYU ET AL: "Efficient deep network for vision-based object detection in robotic applications", NEUROCOMPUTING, vol. 245, 1 July 2017 (2017-07-01), pages 31 - 45, XP029978678, ISSN: 0925-2312, DOI: 10.1016/J.NEUCOM.2017.03.050 *
See also references of WO2019203921A1 *
SUDOWE PATRICK ET AL: "Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video", 20 September 2011, ICIAP: INTERNATIONAL CONFERENCE ON IMAGE ANALYSIS AND PROCESSING, 17TH INTERNATIONAL CONFERENCE, NAPLES, ITALY, SEPTEMBER 9-13, 2013. PROCEEDINGS; [LECTURE NOTES IN COMPUTER SCIENCE; LECT.NOTES COMPUTER], SPRINGER, BERLIN, HEIDELBERG, PAGE(S) 11 - 20, ISBN: 978-3-642-17318-9, XP047370157 *
ZHANG SHANSHAN ET AL: "Towards Reaching Human Performance in Pedestrian Detection", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 40, no. 4, 1 April 2018 (2018-04-01), USA, pages 973 - 986, XP055862337, ISSN: 0162-8828, Retrieved from the Internet <URL:https://ieeexplore.ieee.org/ielx7/34/8306529/07917260.pdf?tp=&arnumber=7917260&isnumber=8306529&ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2Fic3RyYWN0L2RvY3VtZW50Lzc5MTcyNjA/Y2FzYV90b2tlbj1Mc0toVFdlUWQwc0FBQUFBOktMNGJnY1lWR052TWlTLXd0aHA4MUQwbHp6NEZFMmZlMVhYM2hZODBEZ2pEYnRwM0ZjdWlnbkppRUN6dTZoYmE4ZFpf> [retrieved on 20211116], DOI: 10.1109/TPAMI.2017.2700460 *
ZONGQING LU ET AL: "Pedestrian detection aided by scale-discriminative network", 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), IEEE, 6 December 2016 (2016-12-06), pages 1 - 7, XP033066467, DOI: 10.1109/SSCI.2016.7850112 *

Also Published As

Publication number Publication date
WO2019203921A1 (en) 2019-10-24
EP3782075A1 (de) 2021-02-24
CN111801689A (zh) 2020-10-20

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