Using visual and text features for direct marketing on multimedia messaging services domain
Multimedia Tools and Applications
Descriptive visual words and visual phrases for image applications
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Comparing compact codebooks for visual categorization
Computer Vision and Image Understanding
Learning natural scene categories by selective multi-scale feature extraction
Image and Vision Computing
Building contextual visual vocabulary for large-scale image applications
Proceedings of the international conference on Multimedia
Max-margin dictionary learning for multiclass image categorization
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Scale invariant gabor descriptor-based noncooperative iris recognition
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Building descriptive and discriminative visual codebook for large-scale image applications
Multimedia Tools and Applications
Speed up image annotation based on LVQ technique with affinity propagation algorithm
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Optimizing visual vocabularies using soft assignment entropies
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Region Contextual Visual Words for scene categorization
Expert Systems with Applications: An International Journal
Integrated image representation based natural scene classification
Expert Systems with Applications: An International Journal
Learning invariant structure for object identification by using graph methods
Computer Vision and Image Understanding
Semantic hierarchies for image annotation: A survey
Pattern Recognition
Supervised visual vocabulary with category information
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Multi-class object layout with unsupervised image classification and object localization
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Improvements in image categorization using codebook ensembles
Image and Vision Computing
Images as sets of locally weighted features
Computer Vision and Image Understanding
Efficient and Effective Visual Codebook Generation Using Additive Kernels
The Journal of Machine Learning Research
Human action recognition using pyramid vocabulary tree
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Human action recognition under log-euclidean riemannian metric
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Automatic image annotation with cooperation of concept-specific and universal visual vocabularies
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Modulating Shape Features by Color Attention for Object Recognition
International Journal of Computer Vision
Synthesizing queries for handwritten word image retrieval
Pattern Recognition
Supervised learning of Gaussian mixture models for visual vocabulary generation
Pattern Recognition
A Review of Codebook Models in Patch-Based Visual Object Recognition
Journal of Signal Processing Systems
Fast shared boosting for large-scale concept detection
Multimedia Tools and Applications
Approximate gaussian mixtures for large scale vocabularies
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Scene recognition on the semantic manifold
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Object class detection: A survey
ACM Computing Surveys (CSUR)
An experimental study on the universality of visual vocabularies
Journal of Visual Communication and Image Representation
Learning group-based dictionaries for discriminative image representation
Pattern Recognition
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Generic Visual Categorization (GVC) is the pattern classification problem which consists in assigning labels to an image based on its semantic content. This is a challenging task as one has to deal with inherent object/scene variations as well as changes in viewpoint, lighting and occlusion. Several state-of-the-art GVC systems use a vocabulary of visual terms to characterize images with a histogram of visual word counts. We propose a novel practical approach to GVC based on a universal vocabulary, which describes the content of all the considered classes of images, and class vocabularies obtained through the adaptation of the universal vocabulary using class-specific data. The main novelty is that an image is characterized by a set of histograms - one per class - where each histogram describes whether the image content is best modeled by the universal vocabulary or the corresponding class vocabulary. This framework is applied to two types of local image features: low-level descriptors such as the popular SIFT and high-level histograms of word co-occurrences in a spatial neighborhood. It is shown experimentally on two challenging datasets (an in-house database of 19 categories and the PASCAL VOC 2006 dataset) that the proposed approach exhibits state-of-the-art performance at a modest computational cost.