DocumentCode :
3148673
Title :
Kinect-based automatic 3D high-resolution face modeling
Author :
Qi Sun ; Yanlong Tang ; Ping Hu ; Jingliang Peng
Author_Institution :
Taishan Coll., Shandong Univ., Jinan, China
fYear :
2012
fDate :
9-11 Nov. 2012
Firstpage :
1
Lastpage :
4
Abstract :
Microsoft Kinect can be used to capture both depth and color information and has been increasingly used for 3D modeling purposes. However, prior facial modeling methods either are computationally intensive or they generate rough results limited by the low resolution and instability of Kinect. In this paper, we propose a novel scheme for automatically and efficiently constructing a life-like textured 3D high-resolution model for the face of any user in front of a Kinect. Specifically, this scheme is composed of a sequence of steps including head region segmentation, depth and color image registration, resolution enhancement and 3D model fairing. Compared to prior methods, our scheme has a set of distinctive advantages. It can be robust even when the user is in a noisy environment; all the processes are automatic, which means that users need not interactively select feature points, and the energy optimization step is more efficient for fast processing of large-scale dynamic images.
Keywords :
face recognition; image colour analysis; image enhancement; image registration; image resolution; image segmentation; image sensors; image texture; optimisation; solid modelling; 3D model fairing; 3D modeling purposes; Kinect-based automatic 3D high-resolution face modeling; Microsoft Kinect; color image registration; color information; depth image registration; depth information; energy optimization step; head region segmentation; large-scale dynamic images; life-like textured 3D high-resolution model; resolution enhancement; Computational modeling; Educational institutions; Energy resolution; Face; Image resolution; Solid modeling; Kinect; face modeling; super-resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2547-9
Type :
conf
DOI :
10.1109/IASP.2012.6425065
Filename :
6425065
Link To Document :
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