Gesture Identification Model In Traditional Indian Performing Arts By Employing Image Processing Techniques

Jyoti, Swaroopa Shastri
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Abstract

Classical dance forms are an integral part of the Indian culture and heritage. Kathakali is an Indian classical dance composed of complex hand gestures, body moments, facial expressions and background music. Kathakali mudras are difficult to understand common peoples. There are 24 classes of hand gestures. The images of hand mudras of kathakali dance are collected from the dataset. The proposed work explores the possibilities of recognizing classical dance mudras in kathakali dance forms in india. This system has achieved an accuracy of 84% with Convolutional Neural Network for classifying the mudras.
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利用图像处理技术识别印度传统表演艺术中的手势模型
古典舞是印度文化和遗产不可分割的一部分。卡塔卡利舞是一种印度古典舞,由复杂的手势、肢体动作、面部表情和背景音乐组成。卡塔卡利舞的手势一般人很难理解。手势共有 24 种。我们从数据集中收集了卡塔卡利舞的手势图像。所提议的工作探索了识别印度卡塔卡利舞中古典舞手势的可能性。该系统利用卷积神经网络对手势进行分类,准确率达到 84%。
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