Visual structures for image browsing

Content-Based Image Retrieval (CBIR) presents several challenges and has been subject to extensive research from many domains, such as image processing or database systems. Database researchers are concerned with indexing and querying, whereas image processing experts worry about extracting appropriate image descriptors. Comparatively little work has been done on designing user interfaces for CBIR systems. This, in turn, has a profound effect on these systems since the concept of image similarity is strongly influenced by user perception. This paper describes an initial effort to fill this gap, combining recent research in CBIR and Information Visualization, studied from a Human-Computer Interface perspective. It presents two visualization techniques based on Spiral and Concentric Rings implemented in a CBIR system to explore query results. The approach is centered on keeping user focus on both the query image, and the most similar retrieved images. Experiments conducted so far suggest that the proposed visualization strategies improves system usability.

[1]  Marti A. Hearst,et al.  Animated exploration of dynamic graphs with radial layout , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[2]  Benjamin B. Bederson,et al.  Does zooming improve image browsing? , 1999, DL '99.

[3]  Pavel Zezula,et al.  M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.

[4]  L. Costa,et al.  Shape description by image foresting transform , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[5]  Luciano da Fontoura Costa,et al.  A graph-based approach for multiscale shape analysis , 2004, Pattern Recognit..

[6]  Benjamin B. Bederson,et al.  PhotoMesa: a zoomable image browser using quantum treemaps and bubblemaps , 2001, UIST '01.

[7]  Jock D. Mackinlay,et al.  Developing calendar visualizers for the information visualizer , 1994, UIST '94.

[8]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[9]  Kerry Rodden,et al.  Does organisation by similarity assist image browsing? , 2001, CHI.

[10]  Ben Shneiderman,et al.  Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Starfield Displays , 1994 .

[11]  Ed H. Chi,et al.  A taxonomy of visualization techniques using the data state reference model , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[12]  Simone Santini,et al.  Emergent Semantics through Interaction in Image Databases , 2001, IEEE Trans. Knowl. Data Eng..

[13]  Ishwar K. Sethi,et al.  eID: a system for exploration of image databases , 2003, Inf. Process. Manag..

[14]  Marc Alexa,et al.  Visualizing time-series on spirals , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[15]  Shouhong Wang,et al.  Knowledge Discovery Through Self-Organizing Maps: Data Visualization and Query Processing , 2002, Knowledge and Information Systems.

[16]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Qi Tian,et al.  Display Optimization for Image Browsing , 2001, MDIC.

[18]  Michael Stonebraker,et al.  Chabot: Retrieval from a Relational Database of Images , 1995, Computer.

[19]  Luciano da Fontoura Costa,et al.  Effective image retrieval by shape saliences , 2003, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003).

[20]  Daniel A. Keim,et al.  Information Visualization and Visual Data Mining , 2002, IEEE Trans. Vis. Comput. Graph..

[21]  John V. Carlis,et al.  Interactive visualization of serial periodic data , 1998, UIST '98.

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

[23]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[24]  Carla E. Brodley,et al.  Interactive Content-based Image Retrieval Using Relevance Feedback , 2002 .