Query by Image and Video Content: The QBIC System

Research on ways to extend and improve query methods for image databases is widespread. We have developed the QBIC (Query by Image Content) system to explore content-based retrieval methods. QBIC allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns, camera and object motion, and other graphical information. Two key properties of QBIC are (1) its use of image and video content-computable properties of color, texture, shape and motion of images, videos and their objects-in the queries, and (2) its graphical query language, in which queries are posed by drawing, selecting and other graphical means. This article describes the QBIC system and demonstrates its query capabilities. QBIC technology is part of several IBM products. >

[1]  Toshikazu Kato,et al.  Intelligent visual interaction with image database systems-toward the multimedia personal interface , 1991 .

[2]  Akio Nagasaka,et al.  Automatic Video Indexing and Full-Video Search for Object Appearances , 1991, VDB.

[3]  Walter Bender,et al.  Salient video stills: content and context preserved , 1993, MULTIMEDIA '93.

[4]  Edward H. Adelson,et al.  Layered representation for motion analysis , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Christos Faloutsos,et al.  QBIC project: querying images by content, using color, texture, and shape , 1993, Electronic Imaging.

[6]  Yoshinobu Tonomura,et al.  VideoMAP and VideoSpaceIcon: tools for anatomizing video content , 1993, INTERCHI.

[7]  John P. Oakley,et al.  Storage and Retrieval for Image and Video Databases , 1993 .

[8]  Alex Pentland,et al.  Photobook: tools for content-based manipulation of image databases , 1994, Electronic Imaging.

[9]  Harpreet S. Sawhney,et al.  Layered representation of motion video using robust maximum-likelihood estimation of mixture models and MDL encoding , 1995, Proceedings of IEEE International Conference on Computer Vision.

[10]  Harpreet S. Sawhney,et al.  Model-based 2D&3D dominant motion estimation for mosaicing and video representation , 1995, Proceedings of IEEE International Conference on Computer Vision.

[11]  Dragutin Petkovic,et al.  Automatic and semiautomatic methods for image annotation and retrieval in query by image content (QBIC) , 1995, Electronic Imaging.