Off the beaten track: using content-based multimedia similarity search for learning
This event took place on Friday 04 March 2011 at 11:30
Suzanne Little
Electronic media is a valuable and ever increasing resource for information seekers and learners. So much information can be contained in a picture, explained by a diagram or demonstrated in a video clip. But how can you find what you are looking for if you don't understand it well enough to describe it? What can you do if you are faced with a mountain of multimedia learning material? Are there other ways of exploring open educational resources then sticking to the well defined paths of text search and hyperlinks?
This talk will present recent work applying content-based multimedia similarity search to find related educational material by using images to query a collection. It will describe the use of local features in images, 'keypoints', identified using an approach called Scale-Invariant Feature Transforms (SIFT) [1], and the implementation of a nearest neighbour based indexing system to find visually similar images. The resulting content-based media search tool (cbms) has been applied in the context of the SocialLearn project [2] to help users find and explore connected web pages, presentations or documents. It is also the basis of the Spot&Search [3] iPhone application that can be used to explore artwork installations on the OU Walton Hall campus.
[1] http://www.cs.ubc.ca/~lowe/keypoints/
[2] http://www.sociallearn.org
[3] http://spotandsearch.kmi.open.ac.uk
This event took place on Friday 04 March 2011 at 11:30
Suzanne Little
Electronic media is a valuable and ever increasing resource for information seekers and learners. So much information can be contained in a picture, explained by a diagram or demonstrated in a video clip. But how can you find what you are looking for if you don't understand it well enough to describe it? What can you do if you are faced with a mountain of multimedia learning material? Are there other ways of exploring open educational resources then sticking to the well defined paths of text search and hyperlinks?
This talk will present recent work applying content-based multimedia similarity search to find related educational material by using images to query a collection. It will describe the use of local features in images, 'keypoints', identified using an approach called Scale-Invariant Feature Transforms (SIFT) [1], and the implementation of a nearest neighbour based indexing system to find visually similar images. The resulting content-based media search tool (cbms) has been applied in the context of the SocialLearn project [2] to help users find and explore connected web pages, presentations or documents. It is also the basis of the Spot&Search [3] iPhone application that can be used to explore artwork installations on the OU Walton Hall campus.
[1] http://www.cs.ubc.ca/~lowe/keypoints/
[2] http://www.sociallearn.org
[3] http://spotandsearch.kmi.open.ac.uk
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Future Internet is...

To succeed the Future Internet will need to address a number of cross-cutting challenges including:
- Scalability in the face of peer-to-peer traffic, decentralisation, and increased openness
- Trust when government, medical, financial, personal data are increasingly trusted to the cloud, and middleware will increasingly use dynamic service selection
- Interoperability of semantic data and metadata, and of services which will be dynamically orchestrated
- Pervasive usability for users of mobile devices, different languages, cultures and physical abilities
- Mobility for users who expect a seamless experience across spaces, devices, and velocities
Future Internet from KMi.
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