NDLI: Topomorphological approach to automatic posture recognition in ballet dance

Content Provider	IET Digital Library
Author	Saha, Sriparna Konar, Amit
Abstract	The proposed system aims at automatic identification of an unknown dance posture referring to the 20 primitive postures of ballet, simultaneously measuring the proximity of an unknown dance posture to a known primitive. A simple and novel six stage algorithm achieves the desired objective. Skin colour segmentation is performed on the dance postures, the output of which is dilated and is processed to generate skeletons of the original postures. The stick figure diagrams laden with minor irregularities are transubstantiated to generate their affirming minimised skeletons. Each of the 20 postures based on their corresponding Euler number are categorised into five groups. Simultaneously the line integral plots of the dance primitives are determined by performing Radon transform on the minimised skeletons. The line integral plots of the fundamental postures along with their Euler number populate the initial database. The group of an unknown posture is determined based on its Euler number, while successively the unknown posture's line integral plot is compared with the line integral plots of the postures belonging to that group. An empirically determined threshold finally decides on the correctness of the performed posture. While recognising unknown postures, the proposed system registers an overall accuracy of 91.35%.
Starting Page	1002
Ending Page	1011
Page Count	10
ISSN	17519659
Volume Number	9
e-ISSN	17519667
Issue Number	Issue 11, Nov (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/9/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2014.0622
Journal	IET Image Processing
Publisher Date	2015-08-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Posture Recognition Automatic Unknown Dance Posture Identification Ballet Dance Computer Vision And Image Processing Technique Euler Number Fundamental Postures Humanities Image Colour Analysis Image Recognition Image Segmentation Initial Database Integral Plots Integral Transforms Minimised Skeletons Radon Transform Radon Transforms Shape Recognition Six Stage Algorithm Skin Colour Segmentation Stick Figure Diagrams Topomorphological Approach Visual Database
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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