Movie indexing via event detection

The past number of years has seen a large increase in the number of movies, and therefore movie databases, created. As movies are typically quite long, locating relevant clips in these databases is quite difficult unless a well defined index is in place. As movies are creatively made, creating automatic indexing algorithms is a challenging task. However, there are a number of underlying film grammar principles that are universally followed. By detecting and examining the use of these principles, it is possible to extract information about the occurrences of specific events in a movie. This work attempts to completely index a movie by detecting all of the relevant events. The event detection process involves examining the underlying structure of a movie and utilising audiovisual analysis techniques, supported by machine learning algorithms, to extract information based on this structure. This results in a summarised and indexed movie

Automatic parsing of sports videos with grammars

Motivated by the analogies between languages and sports videos, we introduce a novel approach for video parsing with grammars. It utilizes compiler techniques for integrating both semantic annotation and syntactic analysis to generate a semantic index of events and a table of content for a given sports video. The video sequence is first segmented and annotated by event detection with domain knowledge. A grammar-based parser is then used to identify the structure of the video content. Meanwhile, facilities for error handling are introduced which are particularly useful when the results of automatic parsing need to be adjusted. As a case study, we have developed a system for video parsing in the particular domain of TV diving programs. Experimental results indicate the proposed approach is effectiv

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Temporal hybridity: Mixing live video footage with instant replay in real time

Copyright @ 2010 ACMIn this paper we explore the production of streaming media that involves live and recorded content. To examine this, we report on how the production practices and process are conducted through an empirical study of the production of live television, involving the use of live and non-live media under highly time critical conditions. In explaining how this process is managed both as an individual and collective activity, we develop the concept of temporal hybridity to explain the properties of these kinds of production system and show how temporally separated media are used, understood and coordinated. Our analysis is examined in the light of recent developments in computing technology and we present some design implications to support amateur video production.The research was partly made possible by a grant from the Swedish Governmental Agency for Innovation Systems to the Mobile Life VinnExcellence Center, in partnership with SonyEricsson, Ericsson, Microsoft Research, Nokia Research, TeliaSonera and the City of Stockholm

Semi-automatic semantic enrichment of raw sensor data

One of the more recent sources of large volumes of generated data is sensor devices, where dedicated sensing equipment is used to monitor events and happenings in a wide range of domains, including monitoring human biometrics. In recent trials to examine the effects that key moments in movies have on the human body, we fitted fitted with a number of biometric sensor devices and monitored them as they watched a range of dierent movies in groups. The purpose of these experiments was to examine the correlation between humans' highlights in movies as observed from biometric sensors, and highlights in the same movies as identified by our automatic movie analysis techniques. However,the problem with this type of experiment is that both the analysis of the video stream and the sensor data readings are not directly usable in their raw form because of the sheer volume of low-level data values generated both from the sensors and from the movie analysis. This work describes the semi-automated enrichment of both video analysis and sensor data and the mechanism used to query the data in both centralised environments, and in a peer-to-peer architecture when the number of sensor devices grows to large numbers. We present and validate a scalable means of semi-automating the semantic enrichment of sensor data, thereby providing a means of large-scale sensor management

The TREC2001 video track: information retrieval on digital video information

The development of techniques to support content-based access to archives of digital video information has recently started to receive much attention from the research community. During 2001, the annual TREC activity, which has been benchmarking the performance of information retrieval techniques on a range of media for 10 years, included a ”track“ or activity which allowed investigation into approaches to support searching through a video library. This paper is not intended to provide a comprehensive picture of the different approaches taken by the TREC2001 video track participants but instead we give an overview of the TREC video search task and a thumbnail sketch of the approaches taken by different groups. The reason for writing this paper is to highlight the message from the TREC video track that there are now a variety of approaches available for searching and browsing through digital video archives, that these approaches do work, are scalable to larger archives and can yield useful retrieval performance for users. This has important implications in making digital libraries of video information attainable

Dialogue scene detection in movies using low and mid-level visual features

This paper describes an approach for detecting dialogue scenes in movies. The approach uses automatically extracted low- and mid-level visual features that characterise the visual content of individual shots, and which are then combined using a state transition machine that models the shot-level temporal characteristics of the scene under investigation. The choice of visual features used is motivated by a consideration of formal film syntax. The system is designed so that the analysis may be applied in order to detect different types of scenes, although in this paper we focus on dialogue sequences as these are the most prevalent scenes in the movies considered to date

The TREC-2002 video track report

TREC-2002 saw the second running of the Video Track, the goal of which was to promote progress in content-based retrieval from digital video via open, metrics-based evaluation. The track used 73.3 hours of publicly available digital video (in MPEG-1/VCD format) downloaded by the participants directly from the Internet Archive (Prelinger Archives) (internetarchive, 2002) and some from the Open Video Project (Marchionini, 2001). The material comprised advertising, educational, industrial, and amateur films produced between the 1930's and the 1970's by corporations, nonprofit organizations, trade associations, community and interest groups, educational institutions, and individuals. 17 teams representing 5 companies and 12 universities - 4 from Asia, 9 from Europe, and 4 from the US - participated in one or more of three tasks in the 2001 video track: shot boundary determination, feature extraction, and search (manual or interactive). Results were scored by NIST using manually created truth data for shot boundary determination and manual assessment of feature extraction and search results. This paper is an introduction to, and an overview of, the track framework - the tasks, data, and measures - the approaches taken by the participating groups, the results, and issues regrading the evaluation. For detailed information about the approaches and results, the reader should see the various site reports in the final workshop proceedings

Indexing of fictional video content for event detection and summarisation

This paper presents an approach to movie video indexing that utilises audiovisual analysis to detect important and meaningful temporal video segments, that we term events. We consider three event classes, corresponding to dialogues, action sequences, and montages, where the latter also includes musical sequences. These three event classes are intuitive for a viewer to understand and recognise whilst accounting for over 90% of the content of most movies. To detect events we leverage traditional filmmaking principles and map these to a set of computable low-level audiovisual features. Finite state machines (FSMs) are used to detect when temporal sequences of specific features occur. A set of heuristics, again inspired by filmmaking conventions, are then applied to the output of multiple FSMs to detect the required events. A movie search system, named MovieBrowser, built upon this approach is also described. The overall approach is evaluated against a ground truth of over twenty-three hours of movie content drawn from various genres and consistently obtains high precision and recall for all event classes. A user experiment designed to evaluate the usefulness of an event-based structure for both searching and browsing movie archives is also described and the results indicate the usefulness of the proposed approach