Title :
Co-Clustering Image Features and Semantic Concepts
Author :
Rege, Manjeet ; Ming Dong ; Fotouhi, Farshad
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Abstract :
In this paper, we present a novel idea of co-clustering image features and semantic concepts. We accomplish this by modelling user feedback logs and low-level features using a bipartite graph. Our experiments demonstrate that (1) incorporating semantic information achieves better image clustering and (2) feature selection in co-clustering narrows the semantic gap, thus enabling efficient image retrieval.
Keywords :
feature extraction; graph theory; image classification; pattern clustering; bipartite graph; coclustering image feature; image classification; image retrieval; semantic information; Bipartite graph; Clustering algorithms; Feedback; Image databases; Image retrieval; Machine vision; Multimedia databases; Multimedia systems; Pattern recognition; Spatial databases; clustering methods; feedback; graph theory; image classification;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312378
