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MY203832A - A system and method for classifying level of aggressiveness - Google Patents

A system and method for classifying level of aggressiveness

Info

Publication number
MY203832A
MY203832A MYPI2020003251A MYPI2020003251A MY203832A MY 203832 A MY203832 A MY 203832A MY PI2020003251 A MYPI2020003251 A MY PI2020003251A MY PI2020003251 A MYPI2020003251 A MY PI2020003251A MY 203832 A MY203832 A MY 203832A
Authority
MY
Malaysia
Prior art keywords
learning model
rectangular prisms
aggressiveness
video stream
level
Prior art date
Application number
MYPI2020003251A
Inventor
Hock Woon Hon
Shang Li Yuen
Kim Meng Liang
Original Assignee
Mimos Berhad
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 Mimos Berhad filed Critical Mimos Berhad
Priority to MYPI2020003251A priority Critical patent/MY203832A/en
Priority to PCT/MY2020/050159 priority patent/WO2021261985A1/en
Publication of MY203832A publication Critical patent/MY203832A/en

Links

Classifications

    • 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
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
    • G08B29/18—Prevention or correction of operating errors
    • G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
    • G08B29/186—Fuzzy logic; neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/07—Target detection

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Medical Informatics (AREA)
  • Mathematical Physics (AREA)
  • Multimedia (AREA)
  • Computer Security & Cryptography (AREA)
  • Automation & Control Theory (AREA)
  • Data Mining & Analysis (AREA)
  • Fuzzy Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Image Analysis (AREA)

Abstract

The present invention relates to a system (1000) and method for classifying level of aggressiveness. The system is configured to classify an aggressive behaviour into a level of aggressiveness based on a video stream. The system comprises a video acquisition unit (10) configured to acquire at least one video stream from at least one video source, an image processing unit (20) configured to convert the at least one video stream into a sequence of image frames and performs data formatting on the sequence of image frames to generate a plurality of volumetric rectangular prisms and an image representation for each of the volumetric rectangular prisms, a training unit (30) configured to perform data training on the plurality of volumetric rectangular prisms and the image representation of each of the volumetric rectangular prisms using a machine learning model and a deep learning model, and an online inferencing unit (40) configured to perform an online fusion of the machine learning model and the deep learning model.
MYPI2020003251A 2020-06-23 2020-06-23 A system and method for classifying level of aggressiveness MY203832A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
MYPI2020003251A MY203832A (en) 2020-06-23 2020-06-23 A system and method for classifying level of aggressiveness
PCT/MY2020/050159 WO2021261985A1 (en) 2020-06-23 2020-11-18 A system and method for classifying level of aggressiveness

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
MYPI2020003251A MY203832A (en) 2020-06-23 2020-06-23 A system and method for classifying level of aggressiveness

Publications (1)

Publication Number Publication Date
MY203832A true MY203832A (en) 2024-07-19

Family

ID=79281536

Family Applications (1)

Application Number Title Priority Date Filing Date
MYPI2020003251A MY203832A (en) 2020-06-23 2020-06-23 A system and method for classifying level of aggressiveness

Country Status (2)

Country Link
MY (1) MY203832A (en)
WO (1) WO2021261985A1 (en)

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101260847B1 (en) * 2007-02-08 2013-05-06 비헤이버럴 레코그니션 시스템즈, 인코포레이티드 Behavioral recognition system

Also Published As

Publication number Publication date
WO2021261985A1 (en) 2021-12-30

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