The nature of statistical learning theory
The nature of statistical learning theory
NeTra: a toolbox for navigating large image databases
Multimedia Systems - Special issue on video content based retrieval
Graph Embeddings and Laplacian Eigenvalues
SIAM Journal on Matrix Analysis and Applications
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
MindReader: Querying Databases Through Multiple Examples
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Incremental semi-supervised subspace learning for image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Manifold-ranking based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Learning an image manifold for retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
A novel log-based relevance feedback technique in content-based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Semi-Supervised Active Learning Framework for Image Retrieval
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Semantic manifold learning for image retrieval
Proceedings of the 13th annual ACM international conference on Multimedia
Learning image manifolds by semantic subspace projection
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines
IEEE Transactions on Circuits and Systems for Video Technology
Fast active tabu search and its application to image retrieval
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Laplacian regularized D-optimal design for active learning and its application to image retrieval
IEEE Transactions on Image Processing
Hessian optimal design for image retrieval
Pattern Recognition
Hi-index | 0.00 |
Recently, there have been considerable interests in geometric-based methods for image retrieval. These methods consider the image space as a smooth manifold and apply manifold learning techniques to find a Euclidean embedding. Thus, the Euclidean distances in the embedding space can be used as approximations to the geodesic distances on the manifold. A main advantage of these methods is that the relevance feedbacks during retrieval can be naturally incorporated into the system as prior information. In this paper, we consider the retrieval problem as a classification problem on manifold. Instead of learning a distance measure, we aim to learn a classification function on the image manifold. Considering efficiency is a key issue in image retrieval, especially on the Webscale, we propose a novel approach for image retrieval on manifold. This approach is based on a regularized linear regression framework. The local manifold structure and user-provided relevance feedbacks are incorporated into the image retrieval system through a Locality Preserving Regularizer. Extensive experiments are carried out on a large image database which demonstrates the efficiency and effectiveness of the proposed approach.