Towards content-based 3D sign language indexing using segmental M-H model
Towards content-based 3D sign language indexing using segmental M-H model
复制标题
使用分段 M-H 模型实现基于内容的 3D 手语索引
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Kabil Jaballah
中科院分区：
文献类型：
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作者：
Kabil Jaballah
3D手语是一项全新的技术，它提供了基于化身创建3D签名内容的工具。在计算机图形学的进步和与现场手语视频相比的许多其他优势的推动下，3D手语受到了越来越多的关注，许多3D手语场景被记录下来，并用于年轻的聋人教学等多种目的。在突尼斯，我们创建了WebSign，这是一个可以通过化身将任何文本内容翻译成任何手语的系统。在过去的几年里，已经提出了许多类似的系统。不幸的是，创建的内容没有被有效地编目，因此无法以相关的方式检索。本文提出了一种自动3D签名内容索引和匹配的新方法。我们的方法是基于手语参数(手形、位置、方向和运动)的自动分类。在移动-保持模型(MHM)的基础上，提出了一种新的模型来表示识别参数。我们实现了所设计的方法，并在包含来自多个系统的2000多个3D签名场景的资源库上进行了测试。结果令人鼓舞，参数识别率高达90%。
3D sign language is a brand new technology that provides tools to create 3D signed content based on avatars. Pushed by the advances in computer graphics and many other advantages compared with videos of live signers, 3D sign language is getting more interest and lots of 3D signed scenes are being recorded and used for multiple purposes like young deaf teaching. In Tunsia, we created WebSign, a system that translates any textual content into any signed language through an avatar. Many similar systems have been proposed during the past few years. Unfortunately, the created contents are not cataloged efficiently and subsequently could not be retrieved in a relevant way. In this paper, we propose a new approach for automatic 3D signed contents indexing and matching. Our approach is based on classifying automatically sign language parameters (hand shape, location, orientation and movement). We also propose a new model to represent the recognized parameters based on the Mouvement-Hold Model (MHM). We implemented the designed approach and tested it on a repository of more than 2000 3D signed scenes issued from multiple systems. Results are encouraging since they reached up to 90% for the parameters recognition rate.