For content based image retrieval using shape descriptors, most approaches so far extract shape information from a segmentation of the image. Shape features derived based on a specific segmentation are not suitable for images containing complex structures. Further, static segmentation based approaches are useful only for a small set of queries. In this paper we discuss the limitations of such b...

Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performan...

Modeling the characteristics of specific images and individual users is a critical issue in content-based image retrieval but insufficiently addressed by the current retrieval approaches. In this paper, we propose a novel approach to dataadaptive and user-adaptive image retrieval based on the idea of peer indexing—describing an image through semantically relevant peer images. Specifically, we a...

To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intraimage and inter-class semant...

One of the challenges in image and video retrieval is the content-based retrieval of images and videos in the web. Less work has been done in this area, mainly due to scalability issues. For this reason, in this paper we investigate this problem by presenting tools for the characterization of the visual contents on specific web collections and a strategy for the search of faces in the web using...

This paper presents an application of perceptual grouping rules for content-based image retrieval. The semantic interrelationships between different primitive image features are exploited by perceptual grouping to detect the presence of manmade structures. A methodology based on these principles in a Bayesian framework for the retrieval of building images, and the results obtained are presented...

The ImageCLEF Photo Retrieval Task 2009 focused on image retrieval and diversity. A new collection was utilised in this task consisting of approximately half a million images with English annotations. Queries were based on analysing search query logs and two different types were released: one containing information about image clusters; the other without. A total of 19 participants submitted 84...