2017 · 17 citations · 12 references
MusicClassical Dance FormsEngineeringMachine LearningVideo RetrievalVideo InterpretationImage ClassificationImage AnalysisPattern RecognitionIndian HeritageVideo Content AnalysisDanceMachine VisionDance On CameraFeature LearningVideo UnderstandingDeep LearningComputer VisionDance FormsArtsMotion Analysis
Classical dance forms are integral to Indian culture and heritage, and preserving and understanding them is a key issue for digital heritage preservation. The study proposes a novel framework to classify Indian classical dance forms from videos. The framework extracts representations using a Deep Convolutional Neural Network and optical flow, trains them with a multi‑class linear SVM, and evaluates performance on a newly introduced dataset. The framework achieved 75.83 % accuracy on 211 test videos.
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.
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Anupama Mallik, Santanu Chaudhury, Hiranmay Ghosh · Journal on Computing and Cultural Heritage · 2011 · 76 citations