Indian Dance Form Recognition from Videos

A. Bisht, Riya Bora, Goutam Saini, Pushkar Shukla
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引用次数: 11

Abstract

Classical dance forms are an integral part of the Indian culture and heritage. Therefore, preserving and comprehending these dance forms is a relevant problem in context with the digital preservation of the Indian Heritage. In this paper, we propose a novel framework to classify Indian classical dance forms from videos. The representations are then extracted through Deep Convolution Neural Network(DCNN) and Optical Flow. Moreover these representations are trained on a multi-class linear support vector machine(SVM). Furthermore, a novel dataset is introduced to evaluate the performance of the proposed framework. The framework is able to achieve the accuracy of 75.83 % when tested on 211 videos.
从视频中识别印度舞蹈形式
古典舞蹈形式是印度文化和遗产不可分割的一部分。因此,保存和理解这些舞蹈形式是印度遗产数字化保存的一个相关问题。在本文中,我们提出了一个新的框架,从视频分类印度古典舞蹈形式。然后通过深度卷积神经网络(DCNN)和光流提取表征。此外,这些表征在多类线性支持向量机(SVM)上进行训练。此外,还引入了一个新的数据集来评估所提出框架的性能。在211个视频的测试中,该框架的准确率达到了75.83%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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