1. Tool for pictorial contents retrieval IST KA3: Semantic Web Technologies Workshop Zdenek Mikovec, Pavel Slavik Czech Technical University Prague Department of Computer Science and Engineering November 2000 department of computer science and engineering

2. department of computer science and engineering Content motivation, problems & solutions implementation results and future work

3. department of computer science and engineering Motivation, problems & solutions traditional approach to picture information retrieval: histograms, keywords,... problems & solutions –P: pure description of picture structure&semantic –S: introduction of relations among picture objects relations could be of two principal classes: –structural (they reflect visual structure) –functional (they reflect semantic relations among object) –P: efficient information retrieval from pictures –S: information filtering and pictorial information inference –P: query result presentation in a suitable picture format –S: suitable formal description of transformation process

4. department of computer science and engineering Implementation all mentioned requirements could be satisfied by the use of XML and XSL transformation sheets DBS (XML) new relation specification (XSL) spatial specification (XSL) DBS (XML) visualization (XSL) VRML Web CGM requests feedback metric definition filtering information (XQL) DBS (XML) MPEG-7 WebCGM (XML) import (XSL) MPEG-7 1. 2a.2b.3. 4. BROWSING USER description browsers 5. XSL pipeline

5. department of computer science and engineering Results and future work described system –semantic views and filters –simpler querying –corresponds with current trends (MPEG-7) system has been implemented and tested –picture databases on WAP –picture information retrieval for blind people Pre-defined dynamically adapting XSL pipeline DBS new rel. generation DBS Web CGM requests feedback metric definition DBS spatial specification visualiza- tion DBS filtering inform MPE G-7 WebCGM import BROWSIN G USER choose import sheet choose visualization sheet VRML

6. department of computer science and engineering

7. department of computer science and engineering Information inference 7 comedy <movie name="Indiana Jones" 9 action 7 comedy 7 <movie name="Indiana Jones" 8 action 4 trans- formation type.comedy=1 type.action=0.5 funny=type*popularity New information - transformation rules (XSL) Original DBS (XML) DBS with new relations (XML)

8. department of computer science and engineering Filtering information 7 comedy 7 trans- formation movie[funny>"5"] Query - transformation rules (XQL) Original DBS (XML) Filtered DBS (XML) 7 comedy 7 <movie name="Indiana Jones" 8 action 4

9. department of computer science and engineering Non-geometrical to geometrical 7 comedy 7 yellow <movie name="Indiana Jones" 8 action 4 green trans- formation color=blue..red according to @funny New geometrical information - transformation rules Original DBS (XML) DBS with geometrical info (XML) 7 comedy 7 <movie name="Indiana Jones" 8 action 4