VISMap: an interactive image/video retrieval system using visualization and concept maps

Images and videos can be indexed by multiple features at different levels, such as color, texture, motion and text annotation. Organizing this information into a system so that users can query effectively is a challenging and important problem. We present VISMap, a visual information seeking system that extends the traditional query paradigms of query-by-example and query-by-sketch and replaces the models of relevance feedback with principles from information visualization and concept representation. Users no longer perform lengthy "one-shot" queries or rely on hidden relevance feedback mechanisms. Instead, we provide a rich set of tools that allow users to construct personal views of the video database and directly visualize and manipulate various views and comprehend effects of individual query criteria on the final search results. The set of tools include: (1) a feature space browser for feature-based exploration and navigation; (2) a distance map for metric comparison and setting and (3) a novel concept map for query representation and creation.

[1]  Bob J. Wielinga,et al.  Ontology-Based Photo Annotation , 2001, IEEE Intell. Syst..

[2]  Anthony G. Cohn,et al.  Representing and Reasoning with Qualitative Spatial Relations About Regions , 1997 .

[3]  Arif Ghafoor,et al.  Semantic Modeling and Knowledge Representation in Multimedia Databases , 1999, IEEE Trans. Knowl. Data Eng..

[4]  Simone Santini,et al.  Beyond query by example , 1998, MULTIMEDIA '98.

[5]  Frank van Harmelen,et al.  C-OWL: Contextualizing Ontologies , 2003, SEMWEB.

[6]  Dimitris Papadias,et al.  Spatial Relations, Minimum Bounding Rectangles, and Spatial Data Structures , 1997, Int. J. Geogr. Inf. Sci..

[7]  Steffen Staab,et al.  From Manual to Semi-Automatic Semantic Annotation: About Ontology-Based Text Annotation Tools , 2000, SAIC@COLING.

[8]  Masahito Hirakawa,et al.  Knowledge-assisted content-based retrieval for multimedia databases , 1994, 1994 Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[9]  Thomas S. Huang,et al.  Relevance feedback: a power tool for interactive content-based image retrieval , 1998, IEEE Trans. Circuits Syst. Video Technol..

[10]  Yannis Avrithis,et al.  USING CONTEXT AND FUZZY RELATIONS TO INTERPRET MULTIMEDIA CONTENT , 2003 .

[11]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[12]  Michael Kifer,et al.  F-logic: a higher-order language for reasoning about objects, inheritance, and scheme , 1989, SIGMOD '89.

[13]  Ingemar J. Cox,et al.  PicHunter: Bayesian relevance feedback for image retrieval , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[14]  Steffen Staab,et al.  Authoring and annotation of web pages in CREAM , 2002, WWW '02.

[15]  R. Brunelli,et al.  A Survey on Video Indexing , 1996 .

[16]  Shih-Fu Chang,et al.  VideoQ: an automated content based video search system using visual cues , 1997, MULTIMEDIA '97.

[17]  Thomas S. Huang,et al.  Factor graph framework for semantic video indexing , 2002, IEEE Trans. Circuits Syst. Video Technol..

[18]  Thierry Declerck,et al.  The Automatic Generation of Formal Annotations in a Multimedia Indexing and Searching Environment , 2001, HTLKM@ACL.

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

[20]  Giorgos Stamou,et al.  Knowledge – Assisted Video Analysis and Object Detection , 2002 .

[21]  Antonio Torralba,et al.  Context-based vision system for place and object recognition , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

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

[23]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[24]  Yueting Zhuang,et al.  Accommodating hybrid retrieval in a comprehensive video database management system , 2002, IEEE Trans. Multim..

[25]  Ben Shneiderman,et al.  Visual information seeking: tight coupling of dynamic query filters with starfield displays , 1994, CHI '94.