DocumentCode :
2986419
Title :
Human body modelling and tracking using volumetric representation: Selected recent studies and possibilities for extensions
Author :
Tran, Cuong ; Trivedi, Mohan M.
Author_Institution :
Comput. Vision & Robot. Res. Lab., Univ. of California, La Jolla, CA
fYear :
2008
fDate :
7-11 Sept. 2008
Firstpage :
1
Lastpage :
9
Abstract :
Articulated human body modeling and tracking from vision data is an attractive research area with many potential applications. There has been a tremendous amount of related research works in this area. Therefore, having a comprehensive insight into high quality existing works and awareness of the research frontier in the area is essential for follow-up research studies. With that objective, this paper provides a review of the subarea of model based methods for human body modeling and tracking using volumetric (voxel) data. We will focus on analyzing and comparing some recent techniques, especially which are in the past two years, in order to highlight trends in the domain as well as to point out limitations of the current state of the art. Based on this analysis, we will discuss our idea of combining Laplacian Eigenspace (LE) based voxel segmentation [20] and Kinematically Constrained Gaussian mixture model (KC-GMM) method [3] to have a more powerful human body pose estimation system as well as discuss other possibilities for future work.
Keywords :
Gaussian processes; anthropometry; eigenvalues and eigenfunctions; image reconstruction; image representation; image segmentation; pose estimation; Laplacian Eigenspace based voxel segmentation; articulated human body modelling; human body pose estimation system; human body tracking; kinematically constrained Gaussian mixture model; reconstructed voxel data; vision data; volumetric representation; Application software; Biological system modeling; Computer vision; Data mining; Feature extraction; Head; Humans; Image reconstruction; Kinematics; Torso; Vision based; human body pose estimation; markerless; volumetric reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Distributed Smart Cameras, 2008. ICDSC 2008. Second ACM/IEEE International Conference on
Conference_Location :
Stanford, CA
Print_ISBN :
978-1-4244-2664-5
Electronic_ISBN :
978-1-4244-2665-2
Type :
conf
DOI :
10.1109/ICDSC.2008.4635733
Filename :
4635733
Link To Document :
بازگشت