57,891 research outputs found
Unsupervised Understanding of Location and Illumination Changes in Egocentric Videos
Wearable cameras stand out as one of the most promising devices for the
upcoming years, and as a consequence, the demand of computer algorithms to
automatically understand the videos recorded with them is increasing quickly.
An automatic understanding of these videos is not an easy task, and its mobile
nature implies important challenges to be faced, such as the changing light
conditions and the unrestricted locations recorded. This paper proposes an
unsupervised strategy based on global features and manifold learning to endow
wearable cameras with contextual information regarding the light conditions and
the location captured. Results show that non-linear manifold methods can
capture contextual patterns from global features without compromising large
computational resources. The proposed strategy is used, as an application case,
as a switching mechanism to improve the hand-detection problem in egocentric
videos.Comment: Submitted for publicatio
Linking Visual Cortical Development to Visual Perception
Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-97-20333); Office of Naval Research (N00014-95-1-0657
Topic Maps as a Virtual Observatory tool
One major component of the VO will be catalogs measuring gigabytes and
terrabytes if not more. Some mechanism like XML will be used for structuring
the information. However, such mechanisms are not good for information
retrieval on their own. For retrieval we use queries. Topic Maps that have
started becoming popular recently are excellent for segregating information
that results from a query. A Topic Map is a structured network of hyperlinks
above an information pool. Different Topic Maps can form different layers above
the same information pool and provide us with different views of it. This
facilitates in being able to ask exact questions, aiding us in looking for gold
needles in the proverbial haystack. Here we discuss the specifics of what Topic
Maps are and how they can be implemented within the VO framework.
URL: http://www.astro.caltech.edu/~aam/science/topicmaps/Comment: 11 pages, 5 eps figures, to appear in SPIE Annual Meeting 2001
proceedings (Astronomical Data Analysis), uses spie.st
Platonic model of mind as an approximation to neurodynamics
Hierarchy of approximations involved in simplification of microscopic theories, from sub-cellural to the whole brain level, is presented. A new approximation to neural dynamics is described, leading to a Platonic-like model of mind based on psychological spaces. Objects and events in these spaces correspond to quasi-stable states of brain dynamics and may be interpreted from psychological point of view. Platonic model bridges the gap between neurosciences and psychological sciences. Static and dynamic versions of this model are outlined and Feature Space Mapping, a neurofuzzy realization of the static version of Platonic model, described. Categorization experiments with human subjects are analyzed from the neurodynamical and Platonic model points of view
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