WO2022243337A9 - System for detection and management of uncertainty in perception systems, for new object detection and for situation anticipation - Google Patents

System for detection and management of uncertainty in perception systems, for new object detection and for situation anticipation Download PDF

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Publication number
WO2022243337A9
WO2022243337A9 PCT/EP2022/063359 EP2022063359W WO2022243337A9 WO 2022243337 A9 WO2022243337 A9 WO 2022243337A9 EP 2022063359 W EP2022063359 W EP 2022063359W WO 2022243337 A9 WO2022243337 A9 WO 2022243337A9
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WO
WIPO (PCT)
Prior art keywords
uncertainty
detection
map
segment
management
Prior art date
Application number
PCT/EP2022/063359
Other languages
French (fr)
Other versions
WO2022243337A2 (en
WO2022243337A3 (en
Inventor
Ralph Meyfarth
Sven Fuelster
Original Assignee
Deep Safety Gmbh
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 Deep Safety Gmbh filed Critical Deep Safety Gmbh
Priority to CN202280050415.2A priority Critical patent/CN117716395A/en
Priority to EP22730378.1A priority patent/EP4341913A2/en
Publication of WO2022243337A2 publication Critical patent/WO2022243337A2/en
Publication of WO2022243337A3 publication Critical patent/WO2022243337A3/en
Publication of WO2022243337A9 publication Critical patent/WO2022243337A9/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Multimedia (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • Image Analysis (AREA)

Abstract

According to the invention, a perception system is provided that comprises a segmenting neural network (40) and an uncertainty detector (60). The segmenting neural network (40) is configured and trained for segmentation of an input image pixel matrix to thus generate a segment composed of elements that correspond the pixels of the input image pixel matrix. By way of class prediction, each element of the segment map is assigned to one of a plurality of object classes the segmenting neural network is trained for by way of class prediction. Elements being assigned to the same object class form a segment of the segment map. The uncertainty detector (60) is configured to generate an uncertainty score map that is composed of elements that correspond the pixels of the input image pixel matrix. Each element of the uncertainty map has an uncertainty score that is determined by the uncertainty detector and that reflects an amount of uncertainty involved in a class prediction for a corresponding element in the segment map.
PCT/EP2022/063359 2021-05-17 2022-05-17 System for detection and management of uncertainty in perception systems, for new object detection and for situation anticipation WO2022243337A2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202280050415.2A CN117716395A (en) 2021-05-17 2022-05-17 System for detecting and managing uncertainty, new object detection and situation expectations in a perception system
EP22730378.1A EP4341913A2 (en) 2021-05-17 2022-05-17 System for detection and management of uncertainty in perception systems, for new object detection and for situation anticipation

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
EP21174146 2021-05-17
EP21174146.7 2021-05-17
EP21204038.0 2021-10-21
EP21204038 2021-10-21

Publications (3)

Publication Number Publication Date
WO2022243337A2 WO2022243337A2 (en) 2022-11-24
WO2022243337A3 WO2022243337A3 (en) 2023-01-12
WO2022243337A9 true WO2022243337A9 (en) 2023-03-09

Family

ID=82058472

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2022/063359 WO2022243337A2 (en) 2021-05-17 2022-05-17 System for detection and management of uncertainty in perception systems, for new object detection and for situation anticipation

Country Status (2)

Country Link
EP (1) EP4341913A2 (en)
WO (1) WO2022243337A2 (en)

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9201421B1 (en) * 2013-11-27 2015-12-01 Google Inc. Assisted perception for autonomous vehicles
US10803328B1 (en) * 2017-11-15 2020-10-13 Uatc, Llc Semantic and instance segmentation
CA3137030A1 (en) * 2019-05-31 2020-12-03 Maryam ZIAEEFARD Method and processing device for training a neural network
US11314258B2 (en) * 2019-12-27 2022-04-26 Intel Corporation Safety system for a vehicle

Also Published As

Publication number Publication date
WO2022243337A2 (en) 2022-11-24
EP4341913A2 (en) 2024-03-27
WO2022243337A3 (en) 2023-01-12

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