scholarly journals Human Posture Tracking and Classification through Stereo Vision and 3D Model Matching

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Stefano Pellegrini ◽  
Luca Iocchi
2021 ◽  
Vol 132 ◽  
pp. 103520
Author(s):  
Xin Lin ◽  
Kunpeng Zhu ◽  
Min Zhou ◽  
Jerry Ying Hsi Fuh ◽  
Qing-guo Wang

Author(s):  
A. Masiero ◽  
G. Tucci ◽  
A. Conti ◽  
L. Fiorini ◽  
A. Vettore

<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>


Author(s):  
Francesco Caputo ◽  
Egidio D’Amato ◽  
Alessandro Greco ◽  
Immacolata Notaro ◽  
Stefania Spada

Author(s):  
Changchang Wu ◽  
Brian Clipp ◽  
Xiaowei Li ◽  
Jan-Michael Frahm ◽  
Marc Pollefeys
Keyword(s):  
3D Model ◽  

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