WO2022079794A1 - 画像選択装置、画像選択方法、及びプログラム - Google Patents

画像選択装置、画像選択方法、及びプログラム Download PDF

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Publication number
WO2022079794A1
WO2022079794A1 PCT/JP2020/038605 JP2020038605W WO2022079794A1 WO 2022079794 A1 WO2022079794 A1 WO 2022079794A1 JP 2020038605 W JP2020038605 W JP 2020038605W WO 2022079794 A1 WO2022079794 A1 WO 2022079794A1
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WO
WIPO (PCT)
Prior art keywords
image
selection
threshold value
image selection
information
Prior art date
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Ceased
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PCT/JP2020/038605
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English (en)
French (fr)
Japanese (ja)
Inventor
登 吉田
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.)
NEC Corp
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NEC Corp
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Publication date
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Priority to PCT/JP2020/038605 priority Critical patent/WO2022079794A1/ja
Priority to JP2022556718A priority patent/JP7658380B2/ja
Priority to US18/030,651 priority patent/US20230368419A1/en
Publication of WO2022079794A1 publication Critical patent/WO2022079794A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G06V40/23—Recognition of whole body movements, e.g. for sport training
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06T7/74—Determining position or orientation of objects or cameras using feature-based methods involving reference images or patches
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/53—Querying
    • G06F16/532—Query formulation, e.g. graphical querying
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/55—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/77—Determining position or orientation of objects or cameras using statistical methods
    • 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
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
    • G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • 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
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/761—Proximity, similarity or dissimilarity measures
    • 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
    • G06V10/762—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
    • 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
    • G06T2207/20092—Interactive image processing based on input by user
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30196—Human being; Person
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30232—Surveillance

Definitions

  • the computer Using the reference posture information indicating the reference posture, set at least one of the threshold value for selecting at least one target image from the plurality of selection target images and the threshold value for classifying the plurality of selection target images. Threshold setting process and An image selection process for selecting at least one target image from the plurality of selection target images or classifying the plurality of selection target images using the threshold value. An image selection method is provided.
  • (A) is a diagram showing an example of reference posture information
  • (B) and (C) are diagrams showing an example of query information. It is a figure which showed schematically the multidimensional space for explaining the function of the threshold value setting part.
  • the search unit 105 searches for a skeleton structure having a high degree of similarity to the feature amount of the search query (query state) from a plurality of skeleton structures stored in the database 110. It can be said that the search unit 105 searches for the state of a person who corresponds to the search condition (query state) from among the states of a plurality of people based on the feature amount of the skeleton structure as the process of recognizing the state of the person. Similar to classification, similarity is the distance between features of the skeletal structure.
  • Bone B31 and B32 connecting the elbow A41 and the left elbow A42, respectively, connecting the right elbow A41 and the left elbow A42 to the right hand A51 and the left hand A52, respectively, and connecting the neck A2 to the right waist A61 and the left waist A62, respectively.
  • a plurality of images that is, a plurality of images to be selected, which are a population when the image selection unit 630 selects an image
  • the selection target image stored in the image storage unit 640 is repeatedly updated. This update includes both the addition of the selection target image and the deletion of the selection target image, but in general, the number of selection target images stored in the image storage unit 640 increases over time. go.
  • the image storage unit 640 is a part of the search unit 105, that is, the image processing device 10. However, the image storage unit 640 may be located outside the image processing device 10.
  • the image storage unit 640 may be a part of the database 110 described above, or may be provided separately from the database 110.
  • FIG. 45 is a flowchart showing a second example of the process performed by the search unit 105 in this search method.
  • the example shown in this figure is the same as the process shown in FIG. 43 except that the threshold value setting unit 620 generates the reference posture information instead of selecting the reference posture information (step S312).
  • FIG. 46 is a diagram for explaining an example of processing performed by the threshold value setting unit 620 when the user inputs selection information to the image processing device 100.
  • the threshold value setting unit 620 displays a multidimensional space on the screen of the terminal operated by the user. This multidimensional space is also centered on each of the plurality of features that characterize the posture. Then, on this screen, the positions of each of the plurality of selection target images stored in the image storage unit 640 are displayed. Then, the user selects a selection target image to be statistically processed on this screen. In the example shown in this figure, the user selects an area to be statistically processed in the multidimensional space. This area is the area where the user wants to classify the posture in particular detail. Then, the threshold value setting unit 620 generates reference posture information by statistically processing a plurality of selected images to be selected.
  • the threshold setting unit 620 narrows the range of the distance for defining the group as the group gets closer to the reference posture. For example, the threshold value setting unit 620 makes the first threshold value for setting the group closest to the reference posture smaller than the second threshold value for setting the next closest group.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Medical Informatics (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Human Computer Interaction (AREA)
  • Mathematical Physics (AREA)
  • Library & Information Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Psychiatry (AREA)
  • Social Psychology (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
PCT/JP2020/038605 2020-10-13 2020-10-13 画像選択装置、画像選択方法、及びプログラム Ceased WO2022079794A1 (ja)

Priority Applications (3)

Application Number Priority Date Filing Date Title
PCT/JP2020/038605 WO2022079794A1 (ja) 2020-10-13 2020-10-13 画像選択装置、画像選択方法、及びプログラム
JP2022556718A JP7658380B2 (ja) 2020-10-13 2020-10-13 画像選択装置、画像選択方法、及びプログラム
US18/030,651 US20230368419A1 (en) 2020-10-13 2020-10-13 Image selection apparatus, image selection method, and non-transitory computer-readable medium

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Application Number Priority Date Filing Date Title
PCT/JP2020/038605 WO2022079794A1 (ja) 2020-10-13 2020-10-13 画像選択装置、画像選択方法、及びプログラム

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Publication number Priority date Publication date Assignee Title
US11875566B1 (en) * 2023-10-10 2024-01-16 The Florida International University Board Of Trustees Anomalous activity recognition in videos
CN120065907B (zh) * 2025-04-28 2025-07-11 昆山鑫佳宏精密组件有限公司 用于盖板压持的稳定性评估方法及装置

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012181736A (ja) * 2011-03-02 2012-09-20 Panasonic Corp 姿勢推定装置、姿勢推定システム、および姿勢推定方法
JP2016058078A (ja) * 2014-09-05 2016-04-21 ザ・ボーイング・カンパニーＴｈｅ Ｂｏｅｉｎｇ Ｃｏｍｐａｎｙ 連想メモリによって分類されたフレームを使用して位置に対する計量値を取得すること
JP2019091138A (ja) * 2017-11-13 2019-06-13 株式会社日立製作所 画像検索装置、画像検索方法、及び、それに用いる設定画面

Family Cites Families (1)

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Publication number Priority date Publication date Assignee Title
JP2011008522A (ja) 2009-06-25 2011-01-13 Seiko Epson Corp 印刷装置、画像処理装置、画像処理方法およびコンピュータープログラム

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012181736A (ja) * 2011-03-02 2012-09-20 Panasonic Corp 姿勢推定装置、姿勢推定システム、および姿勢推定方法
JP2016058078A (ja) * 2014-09-05 2016-04-21 ザ・ボーイング・カンパニーＴｈｅ Ｂｏｅｉｎｇ Ｃｏｍｐａｎｙ 連想メモリによって分類されたフレームを使用して位置に対する計量値を取得すること
JP2019091138A (ja) * 2017-11-13 2019-06-13 株式会社日立製作所 画像検索装置、画像検索方法、及び、それに用いる設定画面

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