您好，欢迎访问上海市农业科学院 机构知识库！
上海市农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Modalities Combination for Italian Sign Language Extraction and Recognition

文献类型： 会议论文

第一作者： Bassem Seddik

作者： Bassem Seddik 1 ; Sami Gazzah 1 ; Najoua Essoukri Ben Amara 1 ;

作者机构： 1.SAGE Laboratory, National Engineering School of Sousse, Sousse University

关键词： Motion spotting;Action recognition;Fisher vector;Modalities combination;Classification fusion

会议名称： International Conference on Image Analysis and Processing

主办单位：

页码： 710-721

摘要： We propose in this work an approach for the automatic extraction and recognition of the Italian sign language using the RGB, depth and skeletal-joint modalities offered by Microsoft's Kinect sensor. We investigate the best modality combination that improves the human-action spotting and recognition in a continuous stream scenario. For this purpose, we define per modality a complementary feature representation and fuse the decisions of multiple SVM classifiers with probability outputs. We contribute by proposing a multi-scale analysis approach that combines a global Fisher vector representation with a local frame-wise one. In addition we define a temporal segmentation strategy that allows the generation of multiple specialized classifiers. The final decision is obtained using the combination of their results. Our tests have been carried out on the Chalearn gesture challenge dataset, and promising results have been obtained on primary experiments.

分类号： TP391.41-53

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：上海市农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台