Image database visualisations, in particular mapping-based visualisations, provide an interesting approach to accessing image repositories as they are able to overcome some of the drawbacks associated with retrieval based approaches. However, making a mapping-based approach work efficiently on large remote image databases, has yet to be explored. In this paper, we present Web-Based Images Browser (WBIB), a novel system that efficiently employs image pyramids to reduce bandwidth requirements so that users can interactively explore large remote image databases.

Mapping-based visualisations of image databases are well suited to users wanting to survey the overall content of a collection. Given the large amount of image data contained within such visualisations, however, this approach has yet to be applied to large image databases stored remotely. In this technical demonstration, we showcase our Web-Based Images Browser (WBIB). Our novel system makes use of image pyramids so that users can interactively explore mapping-based visualisations of large remote image databases.

Following miniaturisation of cameras and their integration into mobile devices such as smartphones combined with the intensive use of the latter, it is likely that in the near future the majority of digital images will be captured using such devices rather than using dedicated cameras. Since many users decide to keep their photos on their mobile devices, effective methods for managing these image collections are required. Common image browsers prove to be only of limited use, especially for large image sets [1].

Efficient and effective approaches of dealing with the vast amount of visual information available nowadays are highly sought after. This is particularly the case for image collections, both personal and commercial. Due to the magnitude of these ever expanding image repositories, annotation of all images images is infeasible, and search in such an image collection therefore becomes inherently difficult. Although content-based image retrieval techniques have shown much potential, such approaches also suffer from various problems making it difficult to adopt them in practice. In this paper, we follow a different approach, namely that of browsing image databases for image retrieval. In our Honeycomb Image Browser, large image databases are visualised on a hexagonal lattice with image thumbnails occupying hexagons. Arranged in a space filling manner, visually similar images are located close together enabling large image datasets to be navigated in a hierarchical manner. Various browsing tools are incorporated to allow for interactive exploration of the database. Experimental results confirm that our approach affords efficient image retrieval.

In this paper we explore different ways in which large collections of images can be visualised. We discuss the three principle visualisation techniques employed for this purpose, namely dimensionality reduced mappings, clustering-based visualisations and graph-based representations. Mapping-based techniques try to present the relationships between images described by high-dimensional features in a low-dimensional visualisation space. Clustered visualisations group similar images based on content, metadata or time stamp information, while in graph-based approaches links between images are exploited to arrive at an intuitive display of the dataset. We highlight advantages and disadvantages of the various approaches and emphasise the need for a benchmark which allows objective evaluation of these systems.

This paper discusses the use of genetic algorithms and genetic programming within the simulation soccer domain. Genetic algorithms (GAs) are based on the Darwinian theory of evolution and provide techniques to execute an effective search on a large range of potential solutions to a specific problem. Genetic Programming (GP) uses GA concepts to evolve a computer program. We show how GAs and GP have been applied to the challenging real-time and noisy domain of RoboCup simulation soccer. Among others, genetic approaches can be used to find appropriate actions for a soccer agent during a game, to improve different aspects of team strategy as well as to strengthen the ability of a player or a team in training exercises.