Modeling tagged photos for automatic image annotation
Neela Sawant · 2011
A semantic concept can be a physical object (e.g., 'car', 'zebra-fish'), an activity (e.g., 'demonstration', 'running') or an obscure category (e.g., 'historical', 'autumn'). In automatic image annotation, machines are taught to infer such semantic concepts by training with hundreds of manually selected images that contain those concepts. So far, remarkable progress has been made in the areas of visual feature extraction and machine learning algorithms that relate features to concepts. Now the new challenge is to scale the inference and annotation capacity to thousands of semantic concepts in the real world.