{"title":"Crane gesture recognition using pseudo 3-D hidden Markov models","authors":"Stefan Müller, S. Eickeler, G. Rigoll","doi":"10.1109/AFGR.2000.840665","DOIUrl":null,"url":null,"abstract":"A recognition technique based on novel pseudo 3D hidden Markov models, which can integrate spatial as well as temporal derived features is presented. The approach allows the recognition of dynamic gestures such as waving hands as well as static gestures such as standing in a special pose. Pseudo 3D hidden Markov models (P3DHMM) are an extension of the pseudo 2D case, which has been successfully used for the classification of images and the recognition of faces. In the P3DHMM case the so-called superstates contain P2DHMM and thus whole image sequences can be generated by these models. Our approach has been evaluated on a crane signal database, which consists of 12 different predefined gestures for maneuvering cranes.","PeriodicalId":360065,"journal":{"name":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AFGR.2000.840665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
A recognition technique based on novel pseudo 3D hidden Markov models, which can integrate spatial as well as temporal derived features is presented. The approach allows the recognition of dynamic gestures such as waving hands as well as static gestures such as standing in a special pose. Pseudo 3D hidden Markov models (P3DHMM) are an extension of the pseudo 2D case, which has been successfully used for the classification of images and the recognition of faces. In the P3DHMM case the so-called superstates contain P2DHMM and thus whole image sequences can be generated by these models. Our approach has been evaluated on a crane signal database, which consists of 12 different predefined gestures for maneuvering cranes.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
