Hierarchical sparse representation for image retrieval

作者: Linjun Yang , Qi Tian , Bingbing Ni

DOI:

关键词: Image (mathematics)MathematicsU-matrixFeature (computer vision)Image retrievalCodebookLinde–Buzo–Gray algorithmPattern recognitionFeature detection (computer vision)Computer visionArtificial intelligenceSparse approximation

摘要: A hierarchical sparse codebook allows efficient search and comparison of images in image retrieval. The includes multiple levels a gradual determination/classification an feature into one or more groups nodes by traversing the through paths to codebook. is compared with subset at each level codebook, thereby reducing processing time.

参考文章(70)
Jin-Woo Jeong, Kyung-Wook Park, OukSeh Lee, Dong-Ho Lee, Automatic Extraction of Semantic Relationships from Images Using Ontologies and SVM Classifiers Multimedia Content Analysis and Mining. pp. 184- 194 ,(2007) , 10.1007/978-3-540-73417-8_25
Yang Jiangming, Feng Jing, Shuo Wang, Lei Zhang, Toward optimized query suggeston: user interfaces and algorithms ,(2007)
Alberto Belussi, Christos Faloutsos, Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension very large data bases. pp. 299- 310 ,(1995)
Christopher K. Harris, Mauritius A. R. Schmidtler, Effective multi-class support vector machine classification ,(2003)
Tony Lindeberg, Jonas Gårding, Shape-adapted smoothing in estimation of 3-D depth cues from affine distortions of local 2-D brightness structure european conference on computer vision. pp. 389- 400 ,(1994) , 10.1007/3-540-57956-7_42