The Journal of Machine Learning Research
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Probabilistic models for focused web crawling
Proceedings of the 6th annual ACM international workshop on Web information and data management
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Discovering Objects and their Localization in Images
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Learning Hierarchical Models of Scenes, Objects, and Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Efficient MAP approximation for dense energy functions
ICML '06 Proceedings of the 23rd international conference on Machine learning
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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
Using Multiple Segmentations to Discover Objects and their Extent in Image Collections
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A tutorial on spectral clustering
Statistics and Computing
Building descriptive and discriminative visual codebook for large-scale image applications
Multimedia Tools and Applications
Unsupervised action classification using space-time link analysis
Journal on Image and Video Processing
Latent visual context learning for web image applications
Pattern Recognition
Unsupervised Learning for Graph Matching
International Journal of Computer Vision
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This paper proposes a probabilistic approach for unsupervised modeling and recognition of object categories which combines two types of complementary visual evidence, visual contents and inter-connected links between the images. By doing so, our approach not only increases modeling and recognition performance but also provides possible solutions to several problems including modeling of geometric information, computational complexity, and the inherent ambiguity of visual words. Our approach can be incorporated in any generative models, but here we consider two popular models, pLSA and LDA. Experimental results show that the topic models updated by adding link analysis terms significantly improve the standard pLSA and LDA models. Furthermore, we presented competitive performances on unsupervised modeling, ranking of training images, classification of unseen images, and localization tasks with MSRC and PASCAL2005 datasets.