Paper Info
Title
ShapeLab: A Unified Framework for 2D & 3D Shape Retrieval
Abstract
2D or 3D shapes are the most important visual information that we use to recognize an object. We propose a unified framework "ShapeLab" to search similar 2D or 3D shapes from an existing database. Users can search 3D shapes with a 2D input, and vice versa. ShapeLab is composed of four key components: (1) pose determination for 3D models; (2) 2D orthogonal view generation based on multiple levels of detail; (3) similarity measurement between 2D shapes; and (4) freehand sketch-based user interface. Key algorithms supporting the above components are briefly described. Experiments show ShapeLab can provide a better performance such as high accuracy, flexibility and scalability compared to the available methods.
Year
DOI
Venue
2006
10.1109/3DPVT.2006.128
3DPVT
Keywords
Field
DocType
shape retrieval,orthogonal view generation,important visual information,existing database,unified framework,multiple level,freehand sketch-based user interface,available method,better performance,key component,high accuracy,key algorithm,object recognition,image retrieval,graphical user interfaces,level of detail,pose estimation,user interface,information systems,information retrieval,robustness,scalability,user interfaces
Data mining,Computer science,Image retrieval,Robustness (computer science),Pose,Theoretical computer science,Graphical user interface,User interface,Sketch,Scalability,Cognitive neuroscience of visual object recognition
Conference
ISBN
Citations 
PageRank 
0-7695-2825-2
1
0.36
References 
Authors
21
2
Name
Order
Citations
PageRank
Jiantao Pu127723.12
Karthik Ramani2132881.38