论文标题
Bharatanatyam舞蹈转录使用多媒体本体和机器学习
Bharatanatyam Dance Transcription using Multimedia Ontology and Machine Learning
论文作者
论文摘要
印度古典舞蹈是一种超过5000年的多模式语言，用于表达情感。通过多媒体技术保护舞蹈是一项艰巨的任务。在本文中，我们开发了一个系统来生成舞蹈表演的可简化代表。该系统将有助于保留无形的遗产，注释表演以更好地辅导和合成舞蹈表演。我们首先尝试在本体论模型中捕获印度古典舞蹈形式的基本步骤的概念，名为Bharatanatyam Adavus。接下来，我们构建了一个基于事件的低级模型，该模型将Adavus的本体与多模式数据流的本体（在这种情况下为Kinect的RGB-D）进行了本体，以实现计算可实现的框架。最后，本体用于转录到labanotation。我们还提出了一个转录工具，用于编码Bharatanatyam Adavus的性能，以在我们的记录数据集中对其进行测试。我们的主要目的是用本体学记录舞蹈的复杂运动。
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.
