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
effective descriptiveness.
-
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
Back to CAVIAR home page.