Name:
Using metric indexes for efficient content-based multimedia exploration
Start year:
2015
End year:
2017 The multimedia exploration techniques become the most promising trends of the multimedia retrieval, because they allow an intuitive way of accessing the particular content of the multimedia databases. The exploration techniques are useful especially in cases, where traditional methods of data filtering fail or are insufficient. Furthermore, the multimedia exploration is fun! This is beneficial for modern web portals and e-shops containing visually interesting products and advertising, so the portals can keep users attracted for a longer period. The intuitive and funny exploration model is usually simple. However, a simple model cannot resolve the diversity of user's needs. Therefore, in this project we plan to create a complex multimedia exploration framework that is able to intuitively combine multiple similarity models in order to satisfy the particular user's intent. Additionally, we plan to use existing metric indexing structures as the native exploration structures in order to achieve computationally inexpensive and thus fluent exploration. Furthermore, we plan to implement effective multi-query evaluation using specific query objects. This approach is especially viable for cumulative exploration using sophisticated methods of narrowing results and for utilizing exploration movements over the extensive collections (zoom in/out, side movements etc.).