PicHunter: A Bayesian image retrieval system

The Bayesian Image Retrieval System, PicHunter: Theory, Implementation, and Psychophysical Experiments

Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Thomas V. Papathomas, and Peter N. Yianilos
IEEE Transactions on Image Processing, Special Issue on Image and Video Processing for Digital Libraries, 9(1):20--37, 2000

Some later papers which were inspired by this work:

An Optimized Interaction Strategy for Bayesian Relevance Feedback

Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Peter N. Yianilos
IEEE Conference on Computer Vision and Pattern Recognition (CVPR'98)

A new algorithm and systematic evaluation is presented for searching a database via relevance feedback. It represents a new image display strategy for the PicHunter system (Cox, 1996, 1997). The algorithm takes feedback in the form of relative judgments (``item A is more relevant than item B'') as opposed to the stronger assumption of categorical relevance judgments (``item A is relevant but item B is not''). It also exploits a learned probabilistic model of human behavior to make better use of the feedback it obtains. The algorithm can be viewed as an extension of indexing schemes like the k-d tree to a stochastic setting, hence the name ``stochastic-comparison search.'' In simulations, the amount of feedback required for the new algorithm scales like log(|D|), where |D| is the size of the database, while a simple query-by-example approach scales like |D|^a, where a < 1 depends on the structure of the database. This theoretical advantage is reflected by experiments with real users on a database of 1500 stock photographs.

Psychophysical studies of the performance of an image database retrieval system

Thomas V. Papathomas, Tiffany E. Conway, Ingemar J. Cox, Joumana Ghosn, Matthew L. Miller, Thomas P. Minka, and Peter N. Yianilos
IS&T/SPIE Symposium on Electronic Imaging: Science and Technology, Conference on Human Vision and Electronic Imaging III, 1998
(An extended abstract appeared in Investigative Ophthalmology and Visual Science, vol. 39(4), p. S1096, 1998.)

Last modified: Tue Jun 21 10:02:40 GMT 2005