Describing Images Using Qualitative Models and Description Logics

Abstract Our approach describes any digital image qualitatively by detecting regions/objects inside it and describing their visual characteristics (shape and colour) and their spatial characteristics (orientation and topology) by means of qualitative models. The description obtained is translated into a description logic (DL) based ontology, which gives a formal and explicit meaning to the qualitative tags representing the visual features of the objects in the image and the spatial relations between them. For any image, our approach obtains a set of individuals that are classified using a DL reasoner according to the descriptions of our ontology.

[1]  Zia Ul-Qayyum,et al.  Image retrieval through qualitative representations over semantic features , 2007, Multim. Tools Appl..

[2]  Boris Motik,et al.  Query Answering for OWL-DL with Rules , 2004, SEMWEB.

[3]  Bernd Neumann,et al.  Generation of Rules from Ontologies for High-Level Scene Interpretation , 2009, RuleML.

[4]  M. Egenhofer,et al.  Point-Set Topological Spatial Relations , 2001 .

[5]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[6]  Carola Eschenbach,et al.  Formal Ontology in Information Systems , 2008 .

[7]  Andrew U. Frank,et al.  Theories and Methods of Spatio-Temporal Reasoning in Geographic Space , 1992, Lecture Notes in Computer Science.

[8]  Ian Horrocks,et al.  The Even More Irresistible SROIQ , 2006, KR.

[9]  Yarden Katz,et al.  Representing Qualitative Spatial Information in OWL-DL , 2005, OWLED.

[10]  Nicola Guarino,et al.  Sweetening Ontologies with DOLCE , 2002, EKAW.

[11]  Robert Stevens,et al.  OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns , 2004, EKAW.

[12]  Ullrich Hustadt Do we need the closed world assumption in knowledge representation? , 1994, KRDB.

[13]  Gudrun Socher,et al.  Qualitative scene descriptions from images for integrated speech and image understanding , 1997, DISKI.

[14]  Christian Freksa,et al.  Using Orientation Information for Qualitative Spatial Reasoning , 1992, Spatio-Temporal Reasoning.

[15]  Antonio Torralba,et al.  Recognizing indoor scenes , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Boris Motik,et al.  OWL 2: The next step for OWL , 2008, J. Web Semant..

[17]  Yiannis Kompatsiaris,et al.  Trends and Issues in Description Logics Frameworks for Image Interpretation , 2010, SETN.

[18]  A. U. Frank,et al.  Qualitative Spatial Reasoning , 2008, Encyclopedia of GIS.

[19]  Hans W. Guesgen,et al.  Qualitative Spatial and Temporal Reasoning: Emerging Applications, Trends, and Directions , 2011, Spatial Cogn. Comput..

[20]  Peter Gärdenfors,et al.  A grounding framework , 2009, Autonomous Agents and Multi-Agent Systems.

[21]  Jiao Tao,et al.  Integrity Constraints in OWL , 2010, AAAI.

[22]  Boris Motik,et al.  Bridging the gap between OWL and relational databases , 2007, WWW '07.

[23]  M. T. Escrig,et al.  Describing 2 D Objects by using Qualitative Models of Color and Shape at a Fine Level of Granularity , 2008 .

[24]  Max J. Egenhofer,et al.  Reasoning about Gradual Changes of Topological Relationships , 1992, Spatio-Temporal Reasoning.

[25]  Boris Motik,et al.  Closed World Reasoning in the Semantic Web through Epistemic Operators , 2005, OWLED.

[26]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[27]  Bernd Neumann,et al.  On scene interpretation with description logics , 2006, Image Vis. Comput..

[28]  Jiao Tao,et al.  Extending OWL with Integrity Constraints , 2010, Description Logics.

[29]  Sebastian Rudolph,et al.  ELP: Tractable Rules for OWL 2 , 2008, SEMWEB.

[30]  Xiaoping Chen,et al.  Ontology Based Object Categorization for Robots , 2005, PAKM.

[31]  Evren Sirin,et al.  Opening, Closing Worlds - On Integrity Constraints , 2008, OWLED.

[32]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[33]  Jane Hunter,et al.  Adding Multimedia to the Semantic Web: Building an MPEG-7 ontology , 2001, SWWS.

[34]  Jan L. Top,et al.  Engineering ontologies , 1997, Int. J. Hum. Comput. Stud..

[35]  Mehul Bhatt,et al.  A Qualitative Model of Dynamic Scene Analysis and Interpretation in Ambient Intelligence Systems , 2009, Int. J. Robotics Autom..

[36]  Jane Hunter,et al.  Adding Multimedia to the SemanticWeb: Building and Applying an MPEG-7 Ontology , 2005, Multimedia Content and the Semantic Web.

[37]  Kenneth D. Forbus Handbook of Knowledge Representation Edited Qualitative Modeling , 2022 .

[38]  Monique Thonnat,et al.  Ontology based complex object recognition , 2008, Image Vis. Comput..

[39]  Peter Gärdenfors,et al.  Editorial: Cognitive Semantics and Spatio-Temporal Ontologies , 2007, Spatial Cogn. Comput..

[40]  Theoretische Medizin Dissertation zur Erlangung des Grades eines Doktors der Naturwissenschaften , 2009 .

[41]  Stephan Tobies,et al.  Complexity results and practical algorithms for logics in knowledge representation , 2001, ArXiv.

[42]  N. Guarino,et al.  Formal Ontology in Information Systems : Proceedings of the First International Conference(FOIS'98), June 6-8, Trento, Italy , 1998 .

[43]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[44]  Daniel Hernández,et al.  Relative representation of spatial knowledge: the 2-D case , 1990, Forschungsberichte, TU Munich.

[45]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[46]  Anthony G. Cohn,et al.  Image Retrieval through Qualitative Representations over Semantic Features , 2007, BMVC.

[47]  Mary-Anne Williams Representation = Grounded Information , 2008, PRICAI.

[48]  Kenneth D. Forbus,et al.  Efficient Learning of Qualitative Descriptions for Sketch Recognition , 2006 .

[49]  Joana Hois,et al.  A belief-based architecture for scene analysis: From sensorimotor features to knowledge and ontology , 2009, Fuzzy Sets Syst..

[50]  M. Sarifuddin A New Perceptually Uniform Color Space with Associated Color Similarity Measure for Content-Based Image and Video Retrieval , 2005 .

[51]  S. Kosslyn Image and Brain: The Resolution of the Imagery Debate , 1994, Journal of Cognitive Neuroscience.

[52]  Ian Horrocks,et al.  From SHIQ and RDF to OWL: the making of a Web Ontology Language , 2003, J. Web Semant..