Optimizing Metrics Combining Low-Level Visual Descriptors for Image Annotation and Retrieval
Qianni Zhang, Ebroul Izquierdo · 2006
An object oriented approach for key-word based image annotation and classification is presented. It considers combinations of low-level descriptors and suitable metrics to represent and measure similarity between semantically meaningful objects. The objective is to obtain "optimal" metrics based on a linear combination of single metrics and descriptors in a multi-feature space. The proposed approach estimates an optimal linear combination of predefined metrics by applying a Multi-Objective Optimization technique based on a Pareto Archived Evolution Strategy. The proposed approach has been evaluated and tested for annotation of objects in images.