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
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Social Software is...
Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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