Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Classifying Images of Materials: Achieving Viewpoint and Illumination Independence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Performance Analysis in Content-Based Retrieval with Textures
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Mean Shift Based Clustering in High Dimensions: A Texture Classification Example
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
A Sparse Texture Representation Using Local Affine Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Comparison of Affine Region Detectors
International Journal of Computer Vision
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
On-line evolving image classifiers and their application to surface inspection
Image and Vision Computing
Nesterov's iterations for NMF-Based supervised classification of texture patterns
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
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In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, we extract a set of invariant descriptors from each image. The descriptors of all images are vector-quantized to form 'keypoints'. Then we represent the texture images by 'bag-of-keypoints' vectors. By analogy text classification, we use Probabilistic Latent Semantic Indexing (PLSI) and Non-negative Matrix Factorization (NMF) to perform unsupervised classification. The proposed approach is evaluated using the UIUC database which contains significant viewpoint and scale changes. We also report the results for simultaneously classifying 111 texture categories using the Brodatz database. The performances of classifying new images using the parameters learnt from the unannotated image collection are also presented. The experiment results clearly demonstrate that the approach is robust to scale and viewpoint changes, and achieves good classification accuracy even without annotated training set.