Type of Proposal: Paper

Title: Image Retrieval Knowledge and Art History Curriculum in the Digital Age

Keywords: Image retrieval, art history, image seeking behavior

Author: Hsin-liang Chen

Affiliation: Graduate School of Library and Information Science, University of Texas-Austin

Email: chen@gslis.utexas.edu

Contact address: SZB 564, D7000, Austin, TX 78712

Phone: 512-232-9219

Fax: 512-471-3971

 

Images are used intensively in the field of art history.  In a typical art history class, an instructor presents slides to students and they discuss the historical features of the slides.  Instructors get slides from a departmental slide library and students go to the library to find related images from reference materials, journals or monographs.  But computing technology is changing this scenario. Many museums and galleries digitize their collections and mount their digital images online.  With these digital resources, researchers, educators and students in the art history field can retrieve images from collections around the world.   However, these image resources apply different image management schema to control their digital collections and users have to acquire new knowledge to use these image resources. Before retrieving images, a user needs to know how to find appropriate images from different resources by using different skills and strategies.  The new knowledge and skills of using digital image management systems have not been studied comprehensively. 

            Two major indexing approaches--concept-based and content-based--exist in the image retrieval field (Rasmussen, 1997; Chen & Rasmussen, 1999). Many previous studies on art image retrieval focused exclusively on the concept-based approach (Besser, 1990, 1991; Enser, 1995; Enser & McGregor, 1992; Hastings, 1995a, 1995b; Layne, 1994; Markey, 1984, 1988; Petersen, 1990; Tibbo, 1994; Walker & Thoma, 1990; Zheng, 1999). Investigators from the computing technology community are interested in using a variety of approaches with algorithms and artificial intelligence techniques to index and retrieve images (Cawkell, 1994; Chang, 1989; Chang, et al., 1997; Faloutsos et al., 1994; Ma & Manjanath, 1999).

            New technologies have placed the emphasis on automatic image indexing and content-based retrieval, although it is not clear how the retrieval functionality found in these systems correlates with image information needs of real users. The use of image retrieval systems varies in different fields since users have their own specific information-seeking behavior, and need unique features designed for their tasks.  A user-centered study can provide in-depth understanding of the user's information needs and his/her cognitive abilities.  The understanding can be applied to design better user training, tutorials and system functions.  In order to develop such understanding this project studied the user's image retrieval behavior and addressed implications for the curriculum design of the art history field.

This study investigates end-users' image queries by comparing the features of the queries to those identified in previous studies proposed by Enser and McGregor (1992), Jorgensen (1995) and Fidel (1997) in order to discover the utility of these existing features for the art history field and identify any expansions or new features.  It also examines relationships between user search tasks and image query modes.      Enser and McGregor's categories of Unique and Non-unique, and Jorgensen's classes of Location, Literal Object, Art Historical Information, People and People-related Attributes received high degrees of matching by three reviewers. This finding can be applied to add more details to Enser and McGregor's four categories (Unique, Non-unique, Unique with refiners, and Non-unique with refiners) and to re-group Jorgensen's 12 classes of image attributes. 

            This study also found several significant relationships between the participants' retrieval tasks and query modes.  The participants who used fewer keywords from their topic title and topic description had a larger number of keywords or phrases they planned to use.  A significant difference was found between the mean of the search keywords or phrases participants planned to use and the mean of the search keywords or phrases they actually used.  Pearson correlation coefficients also found a significant difference between the describing task and the number of search keywords or phrases participants actually used.  The participants who submitted a higher number of keywords or phrases they planned to use were able to draw more pictures representing their topic title and the participants who had a greater number of keywords or phrases actually used also generated a larger number of post-search drawings.  A significant relationship was found between the level of success for the search results and the percentage of search keywords or phrases participants planned to use drawn from the topic title or topic description. A significant relationship was also found between the level of success and the number of keywords or phrases participants planned to use.  Implications for curriculum design in the art history field, library instruction, image indexing tools and image retrieval system design are proposed.

 

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