Author:
Jean Martinet
Affiliation:
Université Lille 1, France
Keyword(s):
Gaze Tracking, Image Indexing and Retrieval, Weighting Scheme, Human-centered Computing.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Visual Attention and Image Saliency
Abstract:
We present an application of gaze tracking to image and video indexing, in the form of a model for selecting
and weighting Regions of Interest (RoIs). Image/video indexing refers to the process of creating a synthetic
representation of the media, for instance for retrieval purposes. It usually consists in labeling the media
with semantic keywords describing its content. When automatized, this process is based on the analysis of
visual features, which can be extracted either from the whole image or keyframe, or locally from regions.
Since most of the times the whole image is not relevant for indexing (e.g. large flat regions with no specific
semantic interpretation, blur regions, background regions that may not be relevant for retrieval purposes, and
that should be filtered out), it would be preferable to concentrate the labeling process on specific RoIs that
are considered representative of the scene, like the main subjects. The objective of the work presented here is
to take advanta
ge of natural human gaze information in order to define a human-centered Region of Interest
selection and weighting technique in the context of media retrieval.
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