Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
PLSA-based image auto-annotation: constraining the latent space
Proceedings of the 12th annual ACM international conference on Multimedia
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
International Journal of Computer Vision
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Discriminative Kernel-Based Approach to Rank Images from Text Queries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Computerized Annotation of Pictures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image annotation via graph learning
Pattern Recognition
The MIR flickr retrieval evaluation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
A New Baseline for Image Annotation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Annotating images and image objects using a hierarchical dirichlet process model
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
Accurate Image Search Using the Contextual Dissimilarity Measure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning distance functions for image retrieval
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Coloring local feature extraction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative
Proceedings of the international conference on Multimedia information retrieval
Automatic image semantic interpretation using social action and tagging data
Multimedia Tools and Applications
Innovative directions in self-organized distributed multimedia systems
Multimedia Tools and Applications
Graph-based methods for the automatic annotation and retrieval of art prints
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Fusing object detection and region appearance for image-text alignment
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A Multi-Directional Search technique for image annotation propagation
Journal of Visual Communication and Image Representation
Automatic annotation of tagged content using predefined semantic concepts
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Learning class-to-image distance via large margin and l1-norm regularization
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
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Image annotation is an important computer vision problem where the goal is to determine the relevance of annotation terms for images. Image annotation has two main applications: (i) proposing a list of relevant terms to users that want to assign indexing terms to images, and (ii) supporting keyword based search for images without indexing terms, using the relevance estimates to rank images. In this paper we present TagProp, a weighted nearest neighbour model that predicts the term relevance of images by taking a weighted sum of the annotations of the visually most similar images in an annotated training set. TagProp can use a collection of distance measures capturing different aspects of image content, such as local shape descriptors, and global colour histograms. It automatically finds the optimal combination of distances to define the visual neighbours of images that are most useful for annotation prediction. TagProp compensates for the varying frequencies of annotation terms using a term-specific sigmoid to scale the weighted nearest neighbour tag predictions. We evaluate different variants of TagProp with experiments on the MIR Flickr set, and compare with an approach that learns a separate SVM classifier for each annotation term. We also consider using Flickr tags to train our models, both as additional features and as training labels. We find the SVMs to work better when learning from the manual annotations, but TagProp to work better when learning from the Flickr tags. We also find that using the Flickr tags as a feature can significantly improve the performance of SVMs learned from manual annotations.