Hierarchical Combination of Semantic Visual Words for Image Classification and Clustering

摘要

Image classification and image clustering are two important tasks related to image analysis. In this work a two-level hierarchical model for both tasks using a hierarchical combination of image descriptors is presented. The construction of a latent semantic representation for images is also presented and its impact on the results of both tasks for the two-level hierarchical model is evaluated. Experiments have shown the superior performance attained by the hierarchical combination of descriptors when compared to the simple concatenation of them or to the use of single descriptors. The hierarchical combination of a latent semantic representation has presented results similar to the other hierarchical combinations, using only a small fraction of the time and space needed by others, which is interesting specially for those with restrictions of computer power and/or storage space.