使用多媒体本体和机器学习的Bharatanatyam舞蹈转录
Bharatanatyam Dance Transcription using Multimedia Ontology and Machine Learning
摘要：
印度古典舞蹈是一种有着5000多年历史的多模态语言，用于表达情感。利用多媒体技术保存舞蹈是一项具有挑战性的任务。在本文中，我们开发了一个系统来生成一个可解析的表示的舞蹈表演。该系统将有助于保护非物质遗产，注释表演以更好地指导，并合成舞蹈表演。我们首先试图捕捉印度古典舞蹈形式的基本步骤的概念，命名为Bharatanatyam Adavus，在本体论模型。接下来，我们建立了一个基于事件的低层次模型，将Adavus的本体与多模态数据流（在这种情况下是Kinect的RGB-D）的本体联系起来，以实现一个计算可实现的框架。最后，本体用于转录成Labanotation。我们还提出了一个转录工具编码的表现Bharatanatyam Adavus Labanotation和测试我们记录的数据集。我们的主要目的是使用本体论来记录舞蹈的复杂动作。
英文摘要：
Indian Classical Dance is an over 5000 years' old multi-modal language for expressing emotions. Preservation of dance through multimedia technology is a challenging task. In this paper, we develop a system to generate a parseable representation of a dance performance. The system will help to preserve intangible heritage, annotate performances for better tutoring, and synthesize dance performances. We first attempt to capture the concepts of the basic steps of an Indian Classical Dance form, named Bharatanatyam Adavus, in an ontological model. Next, we build an event-based low-level model that relates the ontology of Adavus to the ontology of multi-modal data streams (RGB-D of Kinect in this case) for a computationally realizable framework. Finally, the ontology is used for transcription into Labanotation. We also present a transcription tool for encoding the performances of Bharatanatyam Adavus to Labanotation and test it on our recorded data set. Our primary aim is to document the complex movements of dance in terms of Labanotation using the ontology.
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