Spatially Enhanced Bags of Words for 3D Shape Retrieval
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A Bag of Words Approach for 3D Object Categorization
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Technical opinion: Steering self-learning distance algorithms
Communications of the ACM - Scratch Programming for All
View topics: automatically generated characteristic view for content-based 3D object retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features
Proceedings of the ACM International Conference on Image and Video Retrieval
3D Part identification based on local shape descriptors
PerMIS '08 Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems
Exploring the bag-of-words method for 3D shape retrieval
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Learning Robust Similarity Measures for 3D Partial Shape Retrieval
International Journal of Computer Vision
Local visual patch for 3d shape retrieval
Proceedings of the ACM workshop on 3D object retrieval
Topic modeling for personalized recommendation of volatile items
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Shape google: Geometric words and expressions for invariant shape retrieval
ACM Transactions on Graphics (TOG)
Investigating the bag-of-words method for 3D shape retrieval
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
On the use of implicit shape models for recognition of object categories in 3D data
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
A comparison of methods for non-rigid 3D shape retrieval
Pattern Recognition
Visual vocabulary signature for 3D object retrieval and partial matching
EG 3DOR'09 Proceedings of the 2nd Eurographics conference on 3D Object Retrieval
A robust 3D interest points detector based on Harris operator
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
Learning the compositional structure of man-made objects for 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
Bag of words and local spectral descriptor for 3D partial shape retrieval
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
Feature-Preserved 3D Canonical Form
International Journal of Computer Vision
Extended cone-curvature based salient points detection and 3D model retrieval
Multimedia Tools and Applications
3D point of interest detection via spectral irregularity diffusion
The Visual Computer: International Journal of Computer Graphics
Combining topological and view-based features for 3D model retrieval
Multimedia Tools and Applications
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
Machine Vision and Applications
Compact vectors of locally aggregated tensors for 3D shape retrieval
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
3D-model retrieval using bag-of-features based on closed curves
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
| Hi-index | 0.00 |
This paper develops an efficient new method for 3D partial shape retrieval. First, a Monte Carlo sampling strategy is employed to extract local shape signatures from each 3D model. After vector quantization, these features are represented by using a bag-of-words model. The main contributions of this paper are threefold as follows: 1) a partial shape dissimilarity measure is proposed to rank shapes according to their distances to the input query, without using any timeconsuming alignment procedure; 2) by applying the probabilistic text analysis technique, a highly compact representation "Shape Topics" and accompanying algorithms are developed for efficient 3D partial shape retrieval, the mapping from "Shape Topics" to "object categories" is established using multi-class SVMs; and 3) a method for evaluating the performance of partial shape retrieval is proposed and tested. To our best knowledge, very few existing methods are able to perform well online partial shape retrieval for large 3D shape repositories. Our experimental results are expected to validate the efficacy and effectiveness of our novel approach.