Open AccessSegmentation of An Indian Classical Dance Videos using Different Segmentation Methods.
Author(s) -
Bhavana R Maale,
Dr.Suvarndyal
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i8468.129219
Subject(s) - artificial intelligence , thresholding , segmentation , computer vision , computer science , dance , categorization , image segmentation , frame (networking) , scale space segmentation , pattern recognition (psychology) , image (mathematics) , art , telecommunications , literature
Video to frame conversion features are retrieved to categorize the actions in an Indian classical dance video dataset. The goal is to design an automatic machine learning model that identifies the moves of a dancer in a video. A video is a collection of images of specific movements, hence, features representing shapes and color can be used to interpret the dance steps. Image segmentation based features are capable of representing the shape in varying background conditions. Segmentation has become an important objective in image analysis and computer vision. To segment the images, edge detection, thresholding and region of interest are taken for this study. The proposed system performance is analyzed for total number of 50 different movements taken from Indian classicaldances.Bharatanatyam,Kathak,Kuchipudi,Manipuri,Mo hiniytam Odissi,Kathakali and Satrriya in different background conditions