Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Modern Information Retrieval
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Survey of Content Based 3D Shape Retrieval Methods
SMI '04 Proceedings of the Shape Modeling International 2004
Augmented Reeb Graphs for Content-Based Retrieval of 3D Mesh Models
SMI '04 Proceedings of the Shape Modeling International 2004
SMI '04 Proceedings of the Shape Modeling International 2004
Retrieval of 3D objects by visual similarity
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Machine Learning
Robust 3D Shape Correspondence in the Spectral Domain
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Distinctive regions of 3D surfaces
ACM Transactions on Graphics (TOG)
A spectral approach to shape-based retrieval of articulated 3D models
Computer-Aided Design
Pose-Oblivious Shape Signature
IEEE Transactions on Visualization and Computer Graphics
Retrieving articulated 3-D models using medial surfaces
Machine Vision and Applications
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
Parts-based 3D object classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
On bending invariant signatures for surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D object retrieval with bag-of-region-words
Proceedings of the international conference on Multimedia
Orientation invariant 3D object classification using hough transform based methods
Proceedings of the ACM workshop on 3D object retrieval
Distance metric learning and feature combination for shape-based 3D model retrieval
Proceedings of the ACM workshop on 3D object retrieval
3D model retrieval using weighted bipartite graph matching
Image Communication
Measuring 3D shape similarity by graph-based matching of the medial scaffolds
Computer Vision and Image Understanding
Accurate content-based video copy detection with efficient feature indexing
Proceedings of the 1st ACM International Conference on Multimedia 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
SHREC'10 track: large scale retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'10 track: generic 3D warehouse
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'10 track: non-rigid 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'10 track: range scan retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'11 track: generic shape retrieval
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
3D object retrieval via range image queries based on SIFT descriptors on panoramic views
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
Local goemetrical feature with spatial context for shape-based 3D model retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
SHREC'12 track: sketch-based 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
SHREC'12 track: generic 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
Local geometry adaptive manifold re-ranking for shape-based 3D object retrieval
Proceedings of the 20th ACM international conference on Multimedia
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
Machine Vision and Applications
A comparison of methods for sketch-based 3D shape retrieval
Computer Vision and Image Understanding
3D object retrieval via range image queries in a bag-of-visual-words context
The Visual Computer: International Journal of Computer Graphics
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Our previous shape-based 3D model retrieval algorithm compares 3D shapes by using thousands of local visual features per model. A 3D model is rendered into a set of depth images, and from each image, local visual features are extracted by using the Scale Invariant Feature Transform (SIFT) algorithm by Lowe. To efficiently compare among large sets of local features, the algorithm employs bag-of-features approach to integrate the local features into a feature vector per model. The algorithm outperformed other methods for a dataset containing highly articulated yet geometrically simple 3D models. For a dataset containing diverse and detailed models, the method did only as well as other methods. This paper proposes an improved algorithm that performs equal or better than our previous method for both articulated and rigid but geometrically detailed models. The proposed algorithm extracts much larger number of local visual features by sampling each depth image densely and randomly. To contain computational cost, the method utilizes GPU for SIFT feature extraction and an efficient randomized decision tree for encoding SIFT features into visual words. Empirical evaluation showed that the proposed method is very fast, yet significantly outperforms our previous method for rigid and geometrically detailed models. For the simple yet articulated models, the performance was virtually unchanged.