SG11201909887RA - Methods and apparatuses for recognizing video and training, electronic device and medium - Google Patents

Methods and apparatuses for recognizing video and training, electronic device and medium

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Publication number
SG11201909887RA
SG11201909887RA SG11201909887RA SG11201909887RA SG 11201909887R A SG11201909887R A SG 11201909887RA SG 11201909887R A SG11201909887R A SG 11201909887RA SG 11201909887R A SG11201909887R A SG 11201909887RA
Authority
SG
Singapore
Prior art keywords
video
key frame
frame
features
key
Prior art date
Application number
Inventor
Tangcongrui He
Hongwei Qin
Original Assignee
Beijing Sensetime Technology Development Co Ltd
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 Beijing Sensetime Technology Development Co Ltd filed Critical Beijing Sensetime Technology Development Co Ltd
Publication of SG11201909887RA publication Critical patent/SG11201909887RA/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/48—Matching video sequences
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/253—Fusion techniques of extracted features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H04N5/265—Mixing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • 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
    • G06T2207/10016—Video; Image sequence
    • 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
    • G06T2207/20212—Image combination
    • G06T2207/20221—Image fusion; Image merging

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Software Systems (AREA)
  • Signal Processing (AREA)
  • Computing Systems (AREA)
  • Image Analysis (AREA)

Abstract

METHODS AND APPARATUSES FOR RECOGNIZING VIDEO AND TRAINING, ELECTRONIC DEVICE AND MEDIUM 5 A method and an apparatus for recognizing and training a video, an electronic device and a storage medium include: extracting features of a first key frame in a video; performing fusion on the features of the first key frame and fusion features of a second key frame in the video to obtain fusion features of the first key frame, where a detection sequence of the second key frame in the video precedes that of the first key 10 frame; and performing detection on the first key frame according to the fusion features of the first key frame to obtain an object detection result of the first key frame. Through iterative multi-frame feature fusion, information contained in shared features of these key frames in the video can be enhanced, thereby improving frame recognition accuracy and video recognition efficiency. 15 [Figure 1]
SG11201909887R 2017-12-13 2018-10-16 Methods and apparatuses for recognizing video and training, electronic device and medium SG11201909887RA (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201711329718.5A CN108229336B (en) 2017-12-13 2017-12-13 Video recognition and training method and apparatus, electronic device, program, and medium
PCT/CN2018/110500 WO2019114405A1 (en) 2017-12-13 2018-10-16 Video recognition and training method and apparatus, electronic device and medium

Publications (1)

Publication Number Publication Date
SG11201909887RA true SG11201909887RA (en) 2019-11-28

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
SG11201909887R SG11201909887RA (en) 2017-12-13 2018-10-16 Methods and apparatuses for recognizing video and training, electronic device and medium

Country Status (6)

Country Link
US (1) US10909380B2 (en)
JP (1) JP6837158B2 (en)
KR (1) KR102365521B1 (en)
CN (2) CN108229336B (en)
SG (1) SG11201909887RA (en)
WO (1) WO2019114405A1 (en)

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Publication number Publication date
WO2019114405A1 (en) 2019-06-20
CN110546645B (en) 2023-09-19
CN108229336A (en) 2018-06-29
US20190266409A1 (en) 2019-08-29
KR102365521B1 (en) 2022-02-21
CN110546645A (en) 2019-12-06
JP2020512647A (en) 2020-04-23
JP6837158B2 (en) 2021-03-03
US10909380B2 (en) 2021-02-02
CN108229336B (en) 2021-06-04
KR20190126366A (en) 2019-11-11

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