We discuss Image Sense Discrimination (ISD), and apply a method based on spectral clustering, using multimodal features from the image and text of the embedding web page. We evaluate our method on a new data set of annotated web images, retrieved with ambiguous query terms. Experiments investigate different levels of sense granularity, as well as the impact of text and image features, and global versus local text features.
Sense discrimination for web images was introduced by REF , who used spectral clustering over multimodal features from the images and web text.
Discriminating Image Senses By Clustering With Multimodal Features
International Conference On Computational Linguistics And Annual Meeting Of The Association For Computational Linguistics - Poster Sessions
Computer Science