Background Subtraction of an Indian Classical Dance Videos using Adaptive Temporal Averaging Method

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Mrs. Bhavana R.Maale
Mrs. Bhavana R.Maale
σ
Dr. Suvarna.Nandyal
Dr. Suvarna.Nandyal
α Visvesvaraya Technological University

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Background Subtraction of an Indian Classical Dance Videos using Adaptive Temporal Averaging Method

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Abstract

A slew of motion detection methods have been proposed in recent years. The background includes some constraints such as changes in illumination, shadow, cluttered the background, scene change and speed of dance between hand gestures and body gestures are different. One of the most basic methods for background subtraction is temporal averaging. We looked at a new adaptive thresholding approach in this paper. To identify moving objects in video sequences, an adaptive thresholding is used. Depending upon the speed of the technique we proposed a Gaussian distribution technique. Gaussian distribution done background subtraction depending upon active pixels it differentiates whether it is a background or foreground. The background model’s update rate has been modified to be adaptive and determined by pixel difference. Our aim is to improve the method’s F-measure by making it more adaptable to various scene scenarios. The experiment results are shown and evaluated. The proposed method and the original method’s quality parameters are compared.

References

14 Cites in Article
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mrs. Bhavana R.Maale. 2026. \u201cBackground Subtraction of an Indian Classical Dance Videos using Adaptive Temporal Averaging Method\u201d. Global Journal of Science Frontier Research - I: Interdisciplinary GJSFR-I Volume 22 (GJSFR Volume 22 Issue I1): .

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Indian classical dance research video overview and background analysis.
Issue Cover
GJSFR Volume 22 Issue I1
Pg. 13- 16
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords
Classification
GJSFR-I Classification: DDC Code: 006.37 LCC Code: TA1634
Version of record

v1.2

Issue date

May 25, 2022

Language
en
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Published Article

A slew of motion detection methods have been proposed in recent years. The background includes some constraints such as changes in illumination, shadow, cluttered the background, scene change and speed of dance between hand gestures and body gestures are different. One of the most basic methods for background subtraction is temporal averaging. We looked at a new adaptive thresholding approach in this paper. To identify moving objects in video sequences, an adaptive thresholding is used. Depending upon the speed of the technique we proposed a Gaussian distribution technique. Gaussian distribution done background subtraction depending upon active pixels it differentiates whether it is a background or foreground. The background model’s update rate has been modified to be adaptive and determined by pixel difference. Our aim is to improve the method’s F-measure by making it more adaptable to various scene scenarios. The experiment results are shown and evaluated. The proposed method and the original method’s quality parameters are compared.

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Background Subtraction of an Indian Classical Dance Videos using Adaptive Temporal Averaging Method

Mrs. Bhavana R.Maale
Mrs. Bhavana R.Maale Visvesvaraya Technological University
Dr. Suvarna.Nandyal
Dr. Suvarna.Nandyal

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