Shape-based image retrieval with relevance feedback

The paper proposes an adaptive framework for shape-based image retrieval with relevance feedback. The motivation is to find an adjustable shape representation scheme that can account for feedback information. Relevance feedback is modeled as a dynamic eigenspace decomposition, and is used to classify the database into relevant and irrelevant groups with respect to the query. Eigenvectors of the subspace are updated by optimizing a linear transform with respect to the J₃ class separability criterion. Experimental results show that the proposed approach can effectively capture a user´s perceptual subjectivity