Self-organizing maps
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Efficient geometry-based similarity search of 3D spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
ACM Transactions on Graphics (TOG)
Web-Based 3D Geometry Model Retrieval
World Wide Web
3D zernike descriptors for content based shape retrieval
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face Recognition Using Kernel Based Fisher Discriminant Analysis
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A Geometric Approach to 3D Object Comparison
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Recognizing faces with PCA and ICA
Computer Vision and Image Understanding - Special issue on Face recognition
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Dynamic self-organizing maps with controlled growth for knowledge discovery
IEEE Transactions on Neural Networks
Probabilistic Self-Organizing Graphs
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
3D model comparison using spatial structure circular descriptor
Pattern Recognition
Multivariate Student-t self-organizing maps
Neural Networks
Probabilistic self-organizing maps for qualitative data
Neural Networks
| Hi-index | 0.01 |
In this paper, we propose a novel 3D head model retrieval framework. Specifically, to facilitate better classification and retrieval, the original 3D head model representations are embedded into another kernel feature space in which kernel principal component analysis (kernel PCA) is then performed to search for the optimal basis representation. Based on the extracted nonlinear features, a hierarchical indexing structure for 3D model retrieval is constructed using the hierarchical self organizing map (HSOM). The proposed indexing structure clusters the database into a hierarchy so that head models are partitioned by coarse features initially and then by finer scale features at lower levels. The main motivation of adopting this approach is that subspace technique like kernel PCA provides an elegant mechanism to describe the 3D head models on multiple resolutions based on the choices for reconstruction error and the orthogonal property of the produced eigenvectors. To further enhance the performance, a fuzzy metric between the query and the feature vector associated with each node on the SOMs is adopted instead of the usual Euclidean metric. Only nodes that possess high fuzzy measure values will be considered further for retrieval. In this way, the fuzzy measure approach is able to pick up potential relevant models even though they may be distributed across a number of neighbouring nodes. In addition to model categorization, the topology-preserving property of HSOM also facilitates the exploration of the model database with the possibility for further knowledge discovery. The effectiveness of the proposed approach is verified by a set of simulation examples on a 3D head model database.