Location: Conferences » External contributions » Semantic and Digital Media Technologies

Using Fuzzy DLs to Enhance Semantic Image Analysis

author: Stamatia Dasiopoulou, Multimedia Knowledge Laboratory, CERTH - Centre for Research and Technology Hellas
published: Dec. 18, 2008,   recorded: December 2008,   views: 363
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Research in image analysis has reached a point where detectors can be learned in a generic fashion for a significant number of conceptual entities. The obtained performance however exhibits versatile behaviour, reflecting implications over the training set selection, similarities in visual manifestations of distinct conceptual entities, and appearance variations of the conceptual entities. A factor partially accountable for these limitations relates to the fact that machine learning techniques realise the transition from visual features to conceptual entities based solely on information regarding perceptual features. Hence, a significant part of knowledge is missed. In this paper, we investigate the use of formal semantics in order to benefit from the logical associations between the conceptual entities, and thereby alleviate part of the challenges involved in extracting semantic descriptions. More specifically, a fuzzy DL based reasoning framework is proposed for the extraction of enhanced image descriptions based on an initial set of graded annotations, generated through generic image analysis techniques. Under the proposed reasoning framework, the initial descriptions are integrated at a semantic level, resolving inconsistencies emanating from conflicting descriptions. Furthermore, the descriptions are enriched by means of entailment, resulting in more complete image descriptions. Experimentation in the domain of outdoor images has shown very promising results, demonstrating the added value in terms of accuracy and completeness.

See Also:

Download slides icon Download slides: samt08_dasiopoulou_ufdl_01.pdf (923.6 KB)

Download slides icon Download slides: samt08_dasiopoulou_ufdl_01.ppt (4.6 MB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: