Technical Program

Paper Detail

Session:Indexing and Retrieval
Time:Wednesday, May 19, 15:30 - 17:30
Presentation: Poster
Topic: Image and Multidimensional Signal Processing: Image and Video Indexing and Retrieval
Authors: Azadeh Kushki; University of Toronto 
 Panagiotis Androutsos; University of Toronto 
 Anastasios Venetsanopoulos; University of Toronto 
Abstract: The use of low-level visual features such as colour and shape incontent-based image retrieval system leads to several ambiguities.Specifically, due to the many-to-many mapping between thelow-level feature space and high-level user concepts, a conceptualuser query may not be modelled as a single point in the featurespace. Furthermore, conceptually similar images may not be fallclose to each other in the low-level feature space. This workaddresses these issues by proposing an interactive technique,Query Feedback. This method employs user input to represent ahigh-level conceptual query as various points in the low-levelspace. Thus, similarity to a given conceptual query is obtained asthe fusion of several low-level representations in the featurespace.

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