Paper
17 July 1998 Psychophysical studies of the performance of an image database retrieval system
Thomas V. Papathomas, Tiffany E. Conway, Ingemar J. Cox, Joumana Ghosn, Matt L. Miller, Thomas P. Minka, Peter N. Yianilos
Author Affiliations +
Proceedings Volume 3299, Human Vision and Electronic Imaging III; (1998) https://doi.org/10.1117/12.320149
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
We describe psychophysical experiments conducted to study PicHunter, a content-based image retrieval (CBIR) system. Experiment 1 studies the importance of using (a) semantic information, (2) memory of earlier input and (3) relative, rather than absolute, judgements of image similarity. The target testing paradigm is used in which a user must search for an image identical to a target. We find that the best performance comes from a version of PicHunter that uses only semantic cues, with memory and relative similarity judgements. Second best is use of both pictorial and semantic cues, with memory and relative similarity judgements. Most reports of CBIR systems provide only qualitative measures of performance based on how similar retrieved images are to a target. Experiment 2 puts PicHunter into this context with a more rigorous test. We first establish a baseline for our database by measuring the time required to find an image that is similar to a target when the images are presented in random order. Although PicHunter's performance is measurably better than this, the test is weak because even random presentation of images yields reasonably short search times. This casts doubt on the strength of results given in other reports where no baseline is established.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas V. Papathomas, Tiffany E. Conway, Ingemar J. Cox, Joumana Ghosn, Matt L. Miller, Thomas P. Minka, and Peter N. Yianilos "Psychophysical studies of the performance of an image database retrieval system", Proc. SPIE 3299, Human Vision and Electronic Imaging III, (17 July 1998); https://doi.org/10.1117/12.320149
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Cited by 31 scholarly publications.
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KEYWORDS
Databases

Image retrieval

Image enhancement

Detection and tracking algorithms

Human-machine interfaces

Visualization

Content based image retrieval

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