Uma Murthy

Superimposed image description and retrieval for fish species identification

Fish species identification is critical to the study of fish ecology and management of fisheries. Traditionally, dichotomous keys are used for fish identification. The keys consist of questions about the observed specimen. Answers to these questions lead to more questions till the reader identifies the specimen. However, such keys are incapable of adapting or changing to meet different fish identification approaches, and often do not focus upon distinguishing characteristics favored by many field ecologists and more user-friendly field guides. This makes learning to identify fish difficult for Ichthyology students. Students usually supplement the use of the key with other methods such as making personal notes, drawings, annotated fish images, and more recently, fish information websites, such as Fishbase. Although these approaches provide useful additional content, it is dispersed across heterogeneous sources and can be tedious to access. Also, most of the existing electronic tools have limited support to manage user created content, especially that related to parts of images such as markings on drawings and images and associated notes. We present SuperIDR, a superimposed image description and retrieval tool, developed to address some of these issues. It allows users to associate parts of images with text annotations. Later, they can retrieve images, parts of images, annotations, and image descriptions through text- and content-based image retrieval. We evaluated SuperIDR in an undergraduate Ichthyology class as an aid to fish species identification and found that the use of SuperIDR yielded a higher likelihood of success in species identification than using traditional methods, including the dichotomous key, fish web sites, notes, etc.

Superimposed Information Architecture for Digital Libraries

A variety of software tools commonly used in research and industry allow a user to select (usually contiguous) segments of content to be annotated, referenced, or otherwise distinguished from a containing document. However, digital libraries (DLs) often curate only full documents, not these selected sub-documents. Thus, sub-documents in a DL may not have the full complement of metadata, and they may not be visible using DL browse and search facilities. We are interested in explicit representation of sub-documents in a DL environment. In this paper, we show how sub-documents may be represented and curated. We focus on the explicit representation of what we call a mark- an encapsulated address of a sub-document along with associated context. Our contributions are: a software architecture for representing marks as first-class objects together with regular documents in a DL; and an implementation of our architecture using existing software packages with modest enhancements. This approach provides new capabilities for the DL with minimal modification to tools and interfaces familiar to the DL user.

A teaching tool for parasitology: enhancing learning with annotation and image retrieval

Parasitology is a basic course in life sciences curricula, but up to now it has few computer-assisted teaching tools. We present SuperIDR, a tool which supports annotation and search (based on a textual and a visual description) in the biodiversity domain. In addition, it provides a feature to aid comparison of morphological characteristics among different species. Preliminary results with two experiments show that students found the tool to be very useful, contributing to an alternative learning approach.

SIERRA – a superimposed application for enhanced image description and retrieval

In this demo proposal, we describe our prototype application, SIERRA, which combines text-based and content-based image retrieval and allows users to link together image content of varying document granularity with related data like annotations. To achieve this, we use the concept of superimposed information (SI), which enables users to (a) deal with information of varying granularity (sub-document to complete document), and (b) select or work with information elements at sub-document level while retaining the original context.

Further development of a digital library curriculum: evaluation approaches and new tools

This paper is a follow-up to our ICADL 2006 paper, reporting on our progress over the past year in developing a digital library curriculum. It presents and describes the current curriculum framework, which now includes ten modules and 41 sub-modules. It provides an overview of the curriculum development lifecycle, and our progress through that lifecycle. In particular, it reports on our evaluation of the modules that have been drafted. It concludes with a description of two new technologies - Superimposed Information (SI) to help resource presentation in a module and Visual User model Data Mining (VUDM) to help long-term module upgrade by visualizing the user community and its trends.

Use of subimages in fish species identification: a qualitative study

Many scholarly tasks involve working with subdocuments, or contextualized fine-grain information, i.e., with information that is part of some larger unit. A digital library (DL) facilitates management, access, retrieval, and use of collections of data and metadata through services. However, most DLs do not provide infrastructure or services to support working with subdocuments. Superimposed information (SI) refers to new information that is created to reference subdocuments in existing information resources. We combine this idea of SI with traditional DL services, to define and develop a DL with SI (SI-DL). We explored the use of subimages and evaluated the use of SuperIDR, a prototype SI-DL, in fish species identification, a scholarly task that involves working with subimages. The contexts and strategies of working with subimages in SuperIDR suggest new and enhanced support (SI-DL services) for scholarly tasks that involve working with subimages, including new ways of querying and searching for subimages and associated information. The main conceptual contributions of our work are the insights gained from these findings of the use of subimages and of SuperIDR, which lead to recommendations for the design of digital libraries with superimposed information.

Species identification: fish images with CBIR and annotations

Uma Murthy, Edward A. Fox, and Yinlin Chen Department of Computer Science, Virginia Tech Blacksburg, VA 24061, USA {umurthy, fox, ylchen}@vt.edu Eric Hallerman Department of Fisheries and Wildlife Scienes Virginia Tech Blacksburg, VA 24061, USA ehallerm@vt.edu Ricardo Torres, Evandro J. Ramos, and Tiago R. C. Falcão Institute of Computing University of Campinas Campinas, SP, Brail rtorres@ic.unicamp.br

SuperIDR: A Tool for Fish Identification and Information Retrieval

ABSTRACT Students, fisheries professionals, and the general public may value computer-facilitated assistance for fish identification and access to ecological and life history information. We developed SuperIDR, a software package supporting such applications, by utilizing the search and data retrieval capabilities of digital libraries, as well as key features of tablet PCs. We demonstrated SuperIDR utilizing a database with information on 207 freshwater fishes of Virginia. A user may annotate fish images and identify fishes by using a dichotomous key; searching for key words, similar images, subimages, or annotations on images; or combinations of these approaches. Students using the software demonstrated enhanced ability to correctly identify specimens. Their comments led to improvements, including the addition of new features. The PC-based system for identifying freshwater fishes of Virginia may be downloaded and modified. SuperIDR is a prototype for PC-based species identification applications—the syste...

Pedagogical Enhancements for Information Retrieval Courses

Information retrieval graduate courses have been offered in the Department of Computer Science at Virginia Tech since 1973. Since the early 1990s, the Information Storage and Retrieval course has been improved through a variety of pedagogical enhancements, many of which are reported in this chapter. The teaching and learning philosophy is based on team- and project-based learning, concept mapping, use of open source software, and more recently, use of virtual platforms, such as Second Life. In this chapter, we report on these approaches and the tools employed. Also, we describe three course offerings as case studies, which made use of the aforementioned methods. We hope that our experiences may be of interest to others involved in IR education.