1 January 2001 Psychophysical experiments on the PicHunter image retrieval system
Thomas V. Papathomas, Ingemar J. Cox, Peter N. Yianilos, Matt L. Miller, Thomas P. Minka, Tiffany E. Conway, Joumana Ghosn
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Psychophysical experiments were conducted on PicHunter, a content-based image retrieval (CBIR) experimental prototype with the following properties: (1) Based on a model of how users respond, it uses Bayes’s rule to predict what target users want, given their actions. (2) It possesses an extremely simple user interface. (3) It employs an entropy-based scheme to improve convergence. (4) It introduces a paradigm for assessing the performance of CBIR systems. Experiments 1–3 studied human judgment of image similarity to obtain data for the model. Experiment 4 studied the importance of using: (a) semantic information, (b) memory of earlier input, and (c) relative and absolute judgments of similarity. Experiment 5 tested an approach that we propose for comparing performances of CBIR systems objectively. Finally, experiment 6 evaluated the most informative display-updating scheme that is based on entropy minimization, and confirmed earlier simulation results. These experiments represent one of the first attempts to quantify CBIR performance based on psychophysical studies, and they provide valuable data for improving CBIR algorithms. Even though they were designed with PicHunter in mind, their results can be applied to any CBIR system and, more generally, to any system that involves judgment of image similarity by humans.
©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)
Thomas V. Papathomas, Ingemar J. Cox, Peter N. Yianilos, Matt L. Miller, Thomas P. Minka, Tiffany E. Conway, and Joumana Ghosn "Psychophysical experiments on the PicHunter image retrieval system," Journal of Electronic Imaging 10(1), (1 January 2001). https://doi.org/10.1117/1.1333058
Published: 1 January 2001
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Cited by 5 scholarly publications.
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KEYWORDS
Image retrieval

Databases

Image enhancement

Data modeling

Detection and tracking algorithms

Performance modeling

Digital imaging

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