Gary Geisler

The Open Video Digital Library

a variety of segmentation, indexing, and user interface techniques developed in the Almaden and Watson labs [Ponceleon et al., 1999], and the Digital Video Multimedia Group at Columbia, which has been engaged in several streams of work including efforts to automate video summaries [Chang et al., 1997]. The Multimedia Information Retrieval Group at Dublin City University has been developing the Fischlar Project, which provides broadcast video for the university community. This group has developed innovative user interfaces for Abstract

Open video

The future will bring widespread access to large digital libraries of video. Consequently, a great deal of research is focused on methods of browsing and retrieving digital video. This type of work requires that investigators acquire and digitize video for their studies since the video information retrieval community does not yet have a collection of video for research purposes. There is a clear need for a shared test collection that they can use. This paper provides a framework for such a test collection and describes the Open Video Project that has begun to develop a test collection based on this framework. The proposed test collection is meant to be used to study a wide range of problems, such as tests of algorithms for creating surrogates for video content or interfaces that display result sets from queries. An important challenge in developing such a collection is storing and distributing video objects. This paper is meant to lay out video management issues that may influence distributed storage solutions. More specifically, this paper describes the first phase for creating the test collection, sets guidelines for building the collection, and serves as a basis for discussion to inform subsequent phases and invite research-community involvement.

How fast is too fast? evaluating fast forward surrogates for digital video

To support effective browsing, interfaces to digital video libraries should include video surrogates (i.e., smaller objects that can stand in for the videos in the collection, analogous to abstracts standing in for documents). The current study investigated four variations (i.e., speeds) of one form of video surrogate: a fast forward created by selecting every Nth frame from the full video. In addition, it tested the validity of six measures of user performance when interacting with video surrogates. Forty-five study participants interacted with all four versions of the fast forward surrogate, and completed all six performance tasks with each. Surrogate speed affected performance on four of the measures: object recognition (graphical), action recognition, linguistic gist comprehension (full text), and visual gist comprehension. Based on these results, we recommend a fast forward default speed of 1:64 of the original video keyframes. In addition, users should control the choice of fast forward speed to adjust for content characteristics and personal preferences.

Tagging video: conventions and strategies of the YouTube community

This poster summarizes the results from a quantitative analysis of the tags and associated metadata used to describe more than one million videos by 537,246 contributors at the YouTube video sharing site. Results from this work suggest methodological and design considerations that could enhance the effectiveness of sharing within communities devoted to online video.

Usage derived recommendations for a video digital library

We describe a minimalist methodology to develop usage-based recommender systems for multimedia digital libraries. A prototype recommender system based on this strategy was implemented for the Open Video Project, a digital library of videos that are freely available for download. Sequential patterns of video retrievals are extracted from the projects web download logs and analyzed to generate a network of video relationships. A spreading activation algorithm locates video recommendations by searching for associative paths connecting query-related videos. We evaluate the performance of the resulting system relative to an item-based collaborative filtering technique operating on user profiles extracted from the same log data.

Creating virtual collections in digital libraries: benefits and implementation issues

Digital libraries have the potential to not only duplicate many of the services provided by traditional libraries but to extend them. Basic finding aids such as search and browse are common in most of todays digital libraries. But just as a traditional library provides more than a card catalog and browseable shelves of books, an effective digital library should offer a wider range of services. Using the traditional library concept of special collections as a model, in this paper we propose that explicitly defining sub-collections in the digital library-virtual collections-can benefit both the librarys users and contributors and increase its viability. We first introduce the concept of a virtual collection, outline the costs and benefits for defining such collections, and describe an implementation of collection-level metadata to create virtual collections for two different digital libraries. We conclude by discussing the implications of virtual collections for enhancing interoperability and sharing across digital libraries, such as those that are part of the National SMETE Digital Library.

Video browsing interfaces for the open video project

The Open Video Project is an on-going effort to develop an open source digital video collection that can be used by the research community and ultimately serve an even broader audience. The initial collection contains video or metadata for more than 1600 digitized video segments comprising nearly half a terabyte of content. Our primary goals for this project are to provide free digital video content to people doing a wide variety of research, to develop a collaborative research environment for people interested in digital video, and to provide a testbed for our own video browsing interface work. Each of these goals fit within a broader mission to understand how people think about, seek, and use digital video. This demonstration summarizes the current status of the project through a brief tour of the Open Video web site, describes our current work in developing surrogates to preview video segments, and shows an innovative video browsing interface we are developing.

Open video: A framework for a test collection

The future will bring widespread access to large digital libraries of video. Consequently, a great deal of research is focused on methods of browsing and retrieving digital video. This type of work requires that investigators acquire and digitize video for their studies since the video information retrieval community does not yet have a collection of video for research purposes. There is a clear need for a shared test collection that they can use. This paper provides a framework for such a test collection and describes the Open Video Project that has begun to develop a test collection based on this framework. The proposed test collection is meant to be used to study a wide range of problems, such as tests of algorithms for creating surrogates for video content or interfaces that display result sets from queries. An important challenge in developing such a collection is storing and distributing video objects. This paper is meant to lay out video management issues that may influence distributed storage solutions. More specifically, this paper describes the first phase for creating the test collection, sets guidelines for building the collection, and serves as a basis for discussion to inform subsequent phases and invite research-community involvement.

Developing recommendation services for a digital library with uncertain and changing data

In developing recommendation services for a new digital library called iLumina (www.ilumina-project.org), we are faced with several challenges related to the nature of the data we have available. The availability and consistency of data associated with iLumina is likely to be highly variable. Any recommendation strategy we develop must be able to cope with this fact, while also being robust enough to adapt to additional types of data available over time as the digital library develops. In this paper we describe the challenges we are faced with in developing a system that can provide our users with good, consistent recommendations under changing and uncertain conditions.

Measuring User Performance during Interactions with Digital Video Collections.

With more and more digital videos found online, video retrieval researchers have begun to create various representations or surrogates for digital videos, such as poster frames, storyboards, video skims and fast forwards. How to evaluate the effectiveness of these video surrogates has become an issue for researchers. This paper proposes two general classes of user tasks—recognition tasks and tasks requiring inference—for which performance measures were developed. The measures include graphical object recognition, textual object recognition, action recognition, free-text gist determination, multiple-choice gist determination and visual gist determination. The preliminary results from two user studies applying these six measures are also discussed in this paper.