CAVIAR: Research Objectives
This central research question of CAVIAR (Can
rich local image descriptions from foveal and other image sensors,
selected by a hierarchal visual attention process and
guided and processed using task, scene, function and object contextual
knowledge improve image-based recognition processes?)
leads to several specific research objectives:
To investigate if using log-polar instead of
Cartesian image data gives image features with more
To investigate how contextual knowledge and priming can
focus collection of feature data through a selective
attention mechanism, in terms of both the quality and the
order of feature extraction.
To investigate if feature grouping mechanisms can improve
the recognition rate, and how contextual knowledge can
improve the grouping process.
To investigate how contextual knowledge can be used to
focus invocation of object, situation and context models from a database.
To investigate alternative appearance-based representations,
similarity metrics and
matching strategies for objects, situations and contexts
in order to increase recognition accuracy.
To investigate alternative knowledge-based control strategies
in order to increase recognition speeds and accuracy.
To implement the results of these investigations and integrate
the components into a complete contextual recognition system.
To test the object and situation recognition system on the tasks of
city centre surveillance and customer behaviour analysis.
Date of last update: August 30, 2002
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