41702110
An analysis of image retrieval tasks in the field of art history
This project applied Jorgensen's three image retrieval tasks (1995) and Enser's four models of image retrieval (1995) to investigate end-users' image retrieval tasks and image query modes in the field of art history. Twenty-six undergraduate students majoring in art history were recruited in this study. They were required to finish a term paper including at least 20 images. The participants' image retrieval tasks were collected by pre- and post-search questionnaires, and a post-search interview. There was a significant difference between the mean number of search keywords or phrases participants planned to use and the mean number of search keywords or phrases they actually used. The study found a significant relationship between the level of success for the search results and the percentage of search keywords or phrases drawn from the topic title or topic description participants planned to use. Implications for image indexing tools and image retrieval system design are proposed.
1872726
An analysis of image queries in the field of art history
This study investigates end-users’ image queries by comparing the features of the queries to those identified in previous studies by Enser and McGregor (1992), Jorgensen (1995), and Fidel (1997). Twenty-nine college students majoring in art history were recruited. They were required to finish a term paper including at least 20 images. The participants’ image queries were collected by preand postsearch questionnaires, and three human reviewers mapped these queries into the previously identified features. Enser and McGregor’s categories of Unique and Nonunique, 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, Nonunique, Unique with refiners, and Nonunique with refiners) and to regroup Jorgensen’s 12 classes of image attributes.
10299300
On the development of a fully automated cryosection image registration system
The CCD cryosection images for the male collected in the National Library of Medicine's Visible Human Project were registered through a procedure involving significant human intervention. In addition, several large misalignments were visible in the registered CCD data for the male. To expedite the exploitation of the visible human cryosection data sets, there is a need to develop a highly accurate yet efficient image registration tool. In this paper, we present the current status of the development of such a fully automated registration system. This system is based on the maximization of mutual information criterion. One key issue of this approach is a robust optimization scheme. The method developed in this paper is to estimate the initial search point through segmentations of regions of interest for each cryosection image slice. Experimental results using the 70 mm cryosection image data for the male are presented in this paper.
12630328
Creating a large-scale content-based airphoto image digital library
This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. There are two major contributions: we suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement and image compression, as well as information analysis techniques such as the self-organizing map (SOM) into an effective large-scale geographical image retrieval system. We present two experiments that evaluate the performance of the Gabor-filter-extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
5485929
ITTALKS: A Case Study in the Semantic Web and DAML
Effective use of the vast quantity of information now available on the web will require the use of "Semantic Web" markup languages such as the DARPA Agent Markup Language (DAML). Such languages will enable the automated gathering and processing of much information that is currently available but insufficiently utilized. Effectively, such languages will facilitate the integration of multi-agent systems with the existing information infrastructure. As part of our exploration of Semantic Web technology, and DAML in particular, we have constructed ITTALKS, a web-based system for automatic and intelligent notification of information technology talks. In this paper, we describe the ITTALKS system, and discuss the numerous ways in which the use of Semantic Web concepts and DAML extend its ability to provide an intelligent online service to both the human community and the agents assisting them.
15840540
Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites
Presented is a model of an integrate-and-fire neuron with active dendrites and a spike-timing dependent Hebbian learning rule. The learning algorithm effectively trains the neuron when responding to several types of temporal encoding schemes: temporal code with single spikes, spike bursts and phase coding. The neuron model and learning algorithm are tested on a neural network with a self-organizing map of competitive neurons. The goal of the presented work is to develop computationally efficient models rather than approximating the real neurons. The approach described in this paper demonstrates the potential advantages of using the processing functionalities of active dendrites as a novel paradigm of computing with networks of artificial spiking neurons.
16294852
Interactive volume visualization on a heterogeneous message-passing multicomputer
This paper describes VOL2, an interactive general-purpose volume renderer based on ray casting and implemented on Pixel-Planes 5, a distributed-memory, message-passing multicomputer. VOL2 is a pipelined renderer using image-space task parallelism and object-space data partitioning. We describe the parallelization and load balancing techniques used in order to achieve interactive response and near-real-time frame rates. We also present a number of applications for our system and derive some general conclusions about operation of image-order rendering algorithms on message-passing multicomputers.