A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Embeddings and Laplacian Eigenvalues
SIAM Journal on Matrix Analysis and Applications
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
ACM Transactions on Mathematical Software (TOMS)
Algorithm 583: LSQR: Sparse Linear Equations and Least Squares Problems
ACM Transactions on Mathematical Software (TOMS)
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
Matrix algorithms
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
IEEE Transactions on Knowledge and Data Engineering
Relevance aggregation projections for image retrieval
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Locality condensation: a new dimensionality reduction method for image retrieval
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Contextual Ranking of Database Querying Results: A Statistical Approach
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Laplacian regularized D-optimal design for active learning and its application to image retrieval
IEEE Transactions on Image Processing
Speed up kernel discriminant analysis
The VLDB Journal — The International Journal on Very Large Data Bases
Hessian optimal design for image retrieval
Pattern Recognition
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Image retrieval algorithm based on enhanced relational graph
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part I
Semi-supervised manifold ordinal regression for image ranking
MM '11 Proceedings of the 19th ACM international conference on Multimedia
BASIL: effective near-duplicate image detection using gene sequence alignment
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Classifier-specific intermediate representation for multimedia tasks
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Neighborhood preserving ordinal regression
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Search web images using objects, backgrounds and conditions
Proceedings of the 20th ACM international conference on Multimedia
Query specific fusion for image retrieval
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Image retrieval based on augmented relational graph representation
Applied Intelligence
G-Optimal Feature Selection with Laplacian regularization
Neurocomputing
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Relevance feedback is a well established and effective framework for narrowing down the gap between low-level visual features and high-level semantic concepts in content-based image retrieval. In most of traditional implementations of relevance feedback, a distance metric or a classifier is usually learned from user's provided negative and positive examples. However, due to the limitation of the user's feedbacks and the high dimensionality of the feature space, one is often confront with the issue of the curse of the dimensionality. Recently, several researchers have considered manifold ways to address this issue, such as Locality Preserving Projections, Augmented Relation Embedding, and Semantic Subspace Projection. In this paper, by using techniques from spectral graph embedding and regression, we propose a unified framework, called spectral regression, for learning an image subspace. This framework facilitates the analysis of the differences and connections between the algorithms mentioned above. And more crucially, it provides much faster computation and therefore makes the retrieval system capable of responding to the user's query more efficiently.