Name
Abstract | ||
|---|---|---|
In this paper, we address invariant keypoint-based texture characterization and recognition. Viewing keypoint sets associated with visual textures as realizations of point processes, we investigate probabilistic texture models from multivariate log-Gaussian Cox processes. These models are parameterized by the covariance structure of the spatial patterns. Their implementation initially rely on the construction of a codebook of the visual signatures of keypoints. We discuss invariance properties of the proposed models for texture recognition applications and report a quantitative evaluation for three texture datasets, namely: UIUC, KTH-TIPs and Brodatz. These experiments include a comparison of the performance reached using different methods for keypoint detection and characterization and demonstrate the relevance of the proposed models w.r.t. state-of-the-art methods. We further discuss the main contribution of proposed approach, including the key features of a statistical model and complexity aspects. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CVPR.2011.5995340 | CVPR |
Keywords | Field | DocType |
visual texture,probabilistic texture models,visual signatures,kth-tip,texture datasets,statistical analysis,invariant keypoint based texture recognition,visual textures,complexity aspects,proposed models w,codebook,invariant keypoint based texture characterization,brodatz,computational complexity,multivariate log-gaussian,gaussian processes,multivariate log gaussian cox processes,uiuc,texture recognition application,image texture,probabilistic texture model,keypoint detection,viewing keypoint,invariant keypoint-based texture characterization,statistical model,correlation,estimation,cox process,point process,visualization,detectors,spatial pattern | Computer vision,Pattern recognition,Visualization,Image texture,Computer science,Gaussian,Gaussian process,Statistical model,Artificial intelligence,Probabilistic logic,Codebook,Covariance | Conference |
Volume | Issue | ISSN |
2011 | 1 | 1063-6919 |
ISBN | Citations | PageRank |
978-1-4577-0394-2 | 13 | 0.87 |
References | Authors | |
19 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huu-Giao Nguyen | 1 | 21 | 3.14 |
| Ronan Fablet | 2 | 102 | 6.88 |
| J-M Boucher | 3 | 13 | 0.87 |