Extending relevance feedback with a group-based user interface

Munehiro Nakazato; Thomas S. Huang

doi:10.1117/12.473026

1 July 2002 Extending relevance feedback with a group-based user interface

Munehiro Nakazato, Thomas S. Huang

Proceedings Volume 4862, Internet Multimedia Management Systems III; (2002) https://doi.org/10.1117/12.473026
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States

Abstract

In the traditional user interfaces of Query-by-Example (QbE) in Content-Based Image Retrieval (CBIR), finding good combinations of query examples is essential for successful retrieval. Unfortunately, the traditional user interfaces are not suitable for trying different combinations of query examples. These systems assumed query examples are added incrementally. The only way to refine the query was to add more example images. When no additional example is found in the result set, the search is considered to have converged. Furthermore, no place was provided to hold previous query results. We are developing ImageGrouper, a new interface for Content-based image retrieval. In this system, the users can interactively compare different combinations of query examples by dragging and grouping images on the workspace (Query-by-Group.) Unlike the traditional systems, a group of images is considered as the basic unit of the query. Because the query results are displayed on another pane, the user can quickly review the results. Combining different query results is also easier. ImageGrouper makes possible new image search methods that were difficult in the traditional user interfaces. First, since the user can annotate text information on each group, integration of keyword-based and content-based search becomes easy. Second, by creating a hierarchy of query examples, the user can begin with collecting relatively generic image first, then narrow down the search to more specific images. Finally, the user can create multiple groups of positive examples. Therefore, we can extend relevance feedback algorithms from two-classes problem (positive and negative) to multiple-classes problem (multiple positive and negative classes.)

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Munehiro Nakazato and Thomas S. Huang "Extending relevance feedback with a group-based user interface", Proc. SPIE 4862, Internet Multimedia Management Systems III, (1 July 2002); https://doi.org/10.1117/12.473026

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KEYWORDS

Human-machine interfaces

Image retrieval

Content based image retrieval

Algorithm development

Feature extraction

Databases

Visualization

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