Automatic ground-truth image generation from user tags
T. Tsirelis, Anastasios N. Delopoulos · Research Repository (Delft University of Technology) · 2011
Automatic selection of ground-truth images is very important for the training of image classifiers, like the ones used in concept-based image retrieval. For this purpose, we propose a method which collects a sufficient number of ground-truth images based on their user-assigned tags. The semantic similarity between the tags of the images and the concept is used as a relevancy metric to classify the images in ranked lists. The system is comprised of parts of data pre-processing, WordNet-based synonym retrieval, Natural Language Processing and corpus-based semantic similarity calculations. Experimental results indicate that the proposed method is effective in collecting groundtruth data and that the training of concept classifiers based on this groundtruth leads to effective image retrieval.