Human factors in automatic image retrieval system design and evaluation

Image retrieval is a human-centered task: images are created by people and are ultimately accessed and used by people for human-related activities. In designing image retrieval systems and algorithms, or measuring their performance, it is therefore imperative to consider the conditions that surround both the indexing of image content and the retrieval. This includes examining the different levels of interpretation for retrieval, possible search strategies, and image uses. Furthermore, we must consider different levels of similarity and the role of human factors such as culture, memory, and personal context. This paper takes a human-centered perspective in outlining levels of description, types of users, search strategies, image uses, and human factors that affect the construction and evaluation of automatic content-based retrieval systems, such as human memory, context, and subjectivity.

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