Paper Info
Title
Visual hull-based Geometric Data Compression of 3D Object
Abstract
As image-based 3D modeling is used in a variety of applications, accordingly, the compression of 3D object geometry represented by multiple images becomes an important task. This paper presents a model-based approach to predict the geometric structure of an object using its visual hull. A visual hull is a geometric entity generated by shape-from-silhouette (SFS), and consequently it largely follows the overall shape of the object. The construction of a visual hull is computationally inexpensive and a visual hull can be encoded with relatively small amount of bits because it can be represented with 2D silhouette images. Therefore, when it comes to the predictive compression of object’s geometric data, the visual hull should be an effective predictor. In the proposed method, the geometric structure of an object is represented by a layered depth image (LDI), and a visual hull from the LDI data is computed via silhouette generation and SFS. The geometry of an object is predicted with the computed visual hull, and the visual hull data with its prediction errors are encoded. Simulation results show that the proposed predictive coding based on visual hull outperforms the previous image-based methods and the partial surface-based method.
Year
DOI
Venue
2015
10.1109/TCSVT.2014.2361420
Circuits and Systems for Video Technology, IEEE Transactions  
Keywords
Field
DocType
3D object coding,layered depth image,predictive coding,shape-from-silhouette,visual hull
Compression (physics),Computer vision,Geometric data analysis,Pattern recognition,Visual hull,Visualization,Computer science,Silhouette,Image coding,Predictive coding,Artificial intelligence,Encoding (memory)
Journal
Volume
Issue
ISSN
PP
99
1051-8215
Citations 
PageRank 
References 
1
0.35
21
Authors
4
Name
Order
Citations
PageRank
Sung Soo Hwang1144.28
Wook-Joong Kim2488.00
Jisung Yoo3101.91
Seong-Dae Kim418425.81