TY - CHAP
T1 - Visualisation and browsing of image databases
AU - Plant, William
AU - Schaefer, Gerald
PY - 2011/5/9
Y1 - 2011/5/9
N2 - In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area.
AB - In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area.
UR - http://www.scopus.com/inward/record.url?scp=79955631521&partnerID=8YFLogxK
UR - http://link.springer.com/chapter/10.1007%2F978-3-642-19551-8_1
U2 - 10.1007/978-3-642-19551-8_1
DO - 10.1007/978-3-642-19551-8_1
M3 - Chapter (peer-reviewed)
AN - SCOPUS:79955631521
SN - 978-3-642-19550-1
T3 - Studies in Computational Intelligence
SP - 3
EP - 57
BT - Multimedia analysis, processing and communications
A2 - Lin, Weisi
A2 - Tao, Dacheng
A2 - Kacprzyk, Janusz
A2 - et al, null
PB - Springer
CY - Berlin (DE)
ER -