{"title":"Towards Symmetry Axis based Markerless Motion Capture","authors":"P. Hartmann, S. Kahn, U. Bockholt, Arjan Kuijper","doi":"10.2312/PE/vriphys/vriphys11/073-082","DOIUrl":null,"url":null,"abstract":"A natural interaction with virtual environments is one of the key issues for the usability of Virtual Reality applications. Device-free, intuitive interactions with the virtual world can be achieved by capturing the movements of the user with markerless motion capture. In this work we present a markerless motion capture approach which can be used to estimate the human body pose in real-time with a single depth camera. The presented approach requires neither a 3D shape model of the tracked person nor a training phase in which body shapes are learned a priori. Instead, it analyzes the curvature of the human body to estimate the symmetry axes of the body joints. These symmetry axes are then used to calculate the pose of the tracked human in real-time. The presented approach was evaluated qualitatively with a time-of-flight and a Kinect depth camera. Furthermore, quantitative simulation results show that the proposed approach is promising for depth cameras which can reliably capture the surface curvature (and thus the normals) of a person and which have a resolution of at least 320x240 pixel.","PeriodicalId":446363,"journal":{"name":"Workshop on Virtual Reality Interactions and Physical Simulations","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Virtual Reality Interactions and Physical Simulations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/PE/vriphys/vriphys11/073-082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A natural interaction with virtual environments is one of the key issues for the usability of Virtual Reality applications. Device-free, intuitive interactions with the virtual world can be achieved by capturing the movements of the user with markerless motion capture. In this work we present a markerless motion capture approach which can be used to estimate the human body pose in real-time with a single depth camera. The presented approach requires neither a 3D shape model of the tracked person nor a training phase in which body shapes are learned a priori. Instead, it analyzes the curvature of the human body to estimate the symmetry axes of the body joints. These symmetry axes are then used to calculate the pose of the tracked human in real-time. The presented approach was evaluated qualitatively with a time-of-flight and a Kinect depth camera. Furthermore, quantitative simulation results show that the proposed approach is promising for depth cameras which can reliably capture the surface curvature (and thus the normals) of a person and which have a resolution of at least 320x240 pixel.