IN2013MU02795A - - Google Patents

Info

Publication number
IN2013MU02795A
IN2013MU02795A IN2795MU2013A IN2013MU02795A IN 2013MU02795 A IN2013MU02795 A IN 2013MU02795A IN 2795MU2013 A IN2795MU2013 A IN 2795MU2013A IN 2013MU02795 A IN2013MU02795 A IN 2013MU02795A
Authority
IN
India
Prior art keywords
clusters
feature vectors
individual
frames
dynamic feature
Prior art date
Application number
Inventor
Aniruddha Sinha
Kingshuk Charkravarty
Original Assignee
Tata Consultancy Services 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 Tata Consultancy Services Ltd filed Critical Tata Consultancy Services Ltd
Priority to IN2795MU2013 priority Critical patent/IN2013MU02795A/en
Priority to EP14767085.5A priority patent/EP3039600B1/en
Priority to PCT/IB2014/001377 priority patent/WO2015028856A1/en
Publication of IN2013MU02795A publication Critical patent/IN2013MU02795A/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/231—Hierarchical techniques, i.e. dividing or merging pattern sets so as to obtain a dendrogram
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • 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
    • G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06V40/25—Recognition of walking or running movements, e.g. gait recognition

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computer Security & Cryptography (AREA)
  • Multimedia (AREA)
  • General Engineering & Computer Science (AREA)
  • Social Psychology (AREA)
  • Computer Hardware Design (AREA)
  • Psychiatry (AREA)
  • Health & Medical Sciences (AREA)
  • Human Computer Interaction (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Image Analysis (AREA)

Abstract

The subject matter discloses systems and methods for identification of individuals. The method includes obtaining static and dynamic feature vectors for skeleton data frames of each individual performing a step activity with an arbitrary pattern and in a random path; creating, for the each individual, a first predefined number of clusters of dynamic feature vectors for the frames; creating, for the each individual, a second predefined number of sub-clusters within the each of the clusters of the dynamic feature vectors for the frames associated with the each of the clusters; and determining, for the each individual, a gait-pose feature data set based on computation of a center of the dynamic feature vectors for the frames associated with the each of the sub-clusters, and a mean of the static feature vectors for the frames associated with the each of the clusters, for identifying the individuals.
IN2795MU2013 2013-08-27 2014-07-24 IN2013MU02795A (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
IN2795MU2013 IN2013MU02795A (en) 2013-08-27 2014-07-24
EP14767085.5A EP3039600B1 (en) 2013-08-27 2014-07-24 Pose and sub-pose clustering-based identification of individuals
PCT/IB2014/001377 WO2015028856A1 (en) 2013-08-27 2014-07-24 Pose and sub-pose clustering-based identification of individuals

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IN2795MU2013 IN2013MU02795A (en) 2013-08-27 2014-07-24

Publications (1)

Publication Number Publication Date
IN2013MU02795A true IN2013MU02795A (en) 2015-07-03

Family

ID=51570774

Family Applications (1)

Application Number Title Priority Date Filing Date
IN2795MU2013 IN2013MU02795A (en) 2013-08-27 2014-07-24

Country Status (3)

Country Link
EP (1) EP3039600B1 (en)
IN (1) IN2013MU02795A (en)
WO (1) WO2015028856A1 (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017156577A1 (en) * 2016-03-14 2017-09-21 National Ict Australia Limited Energy harvesting for sensor systems
CN110276375B (en) * 2019-05-14 2021-08-20 嘉兴职业技术学院 Method for identifying and processing crowd dynamic clustering information
CN111046848B (en) * 2019-12-30 2020-12-01 广东省实验动物监测所 Gait monitoring method and system based on animal running platform
CN111950418A (en) * 2020-08-03 2020-11-17 启航汽车有限公司 Gait recognition method, device and system based on leg features and readable storage medium
CN112232224A (en) * 2020-10-19 2021-01-15 西安建筑科技大学 Cross-visual-angle gait recognition method combining LSTM and CNN

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7330566B2 (en) * 2003-05-15 2008-02-12 Microsoft Corporation Video-based gait recognition
MY164004A (en) * 2010-03-11 2017-11-15 Mimos Berhad Method for use in human authentication

Also Published As

Publication number Publication date
EP3039600B1 (en) 2019-02-06
WO2015028856A1 (en) 2015-03-05
EP3039600A1 (en) 2016-07-06

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