• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Machine Vision and Applications >A natural and synthetic corpus for benchmarking of hand gesture recognition systems
【24h】

A natural and synthetic corpus for benchmarking of hand gesture recognition systems

机译：用于基准手势识别系统的自然和综合语料库

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The use of hand gestures offers an alternative to the commonly used human-computer interfaces (i.e. keyboard, mouse, gamepad, voice, etc.), providing a more intuitive way of navigating among menus and in multimedia applications. This paper presents a dataset for the evaluation of hand gesture recognition approaches in human-computer interaction scenarios. It includes natural data and synthetic data from several State of the Art dictionaries. The dataset considers single-pose and multiple-pose gestures, as well as gestures defined by pose and motion or just by motion. Data types include static pose videos and gesture execution videos-performed by a set of eleven users and recorded with a time-of-flight camera-and synthetically generated gesture images. A novel collection of critical factors involved in the creation of a hand gestures dataset is proposed: capture technology, temporal coherence, nature of gestures, representativeness, pose issues and scalability. Special attention is given to the scalability factor, proposing a simple method for the synthetic generation of depth images of gestures, making possible the extension of a dataset with new dictionaries and gestures without the need of recruiting new users, as well as providing more flexibility in the point-of-view selection. The method is validated for the presented dataset. Finally, a separability study of the pose-based gestures of a dictionary is performed. The resulting corpus, which exceeds in terms of representativity and scalability the datasets existing in the State Of Art, provides a significant evaluation scenario for different kinds of hand gesture recognition solutions.
机译：手势的使用为常用的人机界面（即键盘，鼠标，游戏板，语音等）提供了一种替代方法，从而提供了一种在菜单之间和多媒体应用程序中导航的更直观的方法。本文提出了一个用于评估人机交互场景中手势识别方法的数据集。它包括来自几个最新词典的自然数据和综合数据。数据集考虑单姿势和多姿势手势，以及由姿势和动作或仅由动作定义的手势。数据类型包括静态姿势视频和手势执行视频（由一组11个用户执行并用飞行时间相机记录）以及合成生成的手势图像。提出了涉及手势数据集创建的关键因素的新颖集合：捕获技术，时间连贯性，手势性质，代表性，姿势问题和可伸缩性。对可伸缩性因素给予了特别的关注，提出了一种简单的方法来合成手势的深度图像，生成具有新字典和手势的数据集扩展而无需招募新用户，并提供了更大的灵活性。观点选择。该方法已针对所提供的数据集进行了验证。最后，对字典中基于姿势的手势进行了可分离性研究。由此产生的语料库，在代表性和可伸缩性方面超过了现有技术中现有的数据集，为不同种类的手势识别解决方案提供了重要的评估方案。

著录项

  • 来源
    《Machine Vision and Applications》 |2014年第4期|943-954|共12页
  • 作者

    Javier Molina; Jose A. Pajuelo; Marcos Escudero-Vinolo; Jesus Bescos; Jose M. Martinez;

  • 作者单位

    Video Processing and Understanding Lab Laboratorio C- 111 Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Ciudad Universitaria de Cantoblanco, Ctra. de Colmenar Viejo, km 15, 28049 Madrid, Spain;

    Video Processing and Understanding Lab Laboratorio C- 111 Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Ciudad Universitaria de Cantoblanco, Ctra. de Colmenar Viejo, km 15, 28049 Madrid, Spain;

    Video Processing and Understanding Lab Laboratorio C- 111 Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Ciudad Universitaria de Cantoblanco, Ctra. de Colmenar Viejo, km 15, 28049 Madrid, Spain;

    Video Processing and Understanding Lab Laboratorio C- 111 Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Ciudad Universitaria de Cantoblanco, Ctra. de Colmenar Viejo, km 15, 28049 Madrid, Spain;

    Video Processing and Understanding Lab Laboratorio C- 111 Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Ciudad Universitaria de Cantoblanco, Ctra. de Colmenar Viejo, km 15, 28049 Madrid, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hand gesture dataset; Hand gesture recognition; Pose-based; Motion-based; Human-computer interaction;

    机译：手势数据集;手势识别;基于姿势;基于运动;人机交互;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号