A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Matching 3D Models with Shape Distributions
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
A Survey of Content Based 3D Shape Retrieval Methods
SMI '04 Proceedings of the Shape Modeling International 2004
SMI '04 Proceedings of the Shape Modeling International 2004
Detecting Irregularities in Images and in Video
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
Content-based retrieval of 3D models
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
3D model comparison using spatial structure circular descriptor
Pattern Recognition
A Bayesian 3-D Search Engine Using Adaptive Views Clustering
IEEE Transactions on Multimedia
Combining Topological and Geometrical Features for Global and Partial 3-D Shape Retrieval
IEEE Transactions on Multimedia
Less is More: Efficient 3-D Object Retrieval With Query View Selection
IEEE Transactions on Multimedia
| Hi-index | 0.00 |
The view-based 3D model retrieval systems represent a 3D model using its projected views, and retrieve 3D models by comparing the projected views. Most of the existing view-based 3D model retrieval systems only analyze the features of the projected views, while the spatial arrangements of the viewpoints are not well considered. In this paper, we propose a new 3D model descriptor called sphere image, which is defined as a sphere with a large number of viewpoints distributed on it. Each viewpoint is regarded as a "pixel", associated with a projected view. The feature of the projected view is quantized into a vector, regarded as the "intensity". We also propose a probabilistic graphical model for 3D model matching, and develop a 3D model retrieval system to test our approach. The proposed approach was evaluated on the Princeton shape benchmark. Experimental results indicate that our approach outperforms most of the existing 3D model retrieval systems in respect of retrieval precision and computation cost.