Institutions
|
About Us
|
Help
|
Gaeilge
0
1000
Home
Browse
Advanced Search
Search History
Marked List
Statistics
A
A
A
Author(s)
Institution
Publication types
Funder
Year
Limited By:
Author = Murphy, Noel;
56 items found
Sort by
Title
Author
Item type
Date
Institution
Peer review status
Language
Order
Ascending
Descending
25
50
100
per page
1
2
3
Bibtex
CSV
EndNote
RefWorks
RIS
XML
Displaying Results 1 - 25 of 56 on page 1 of 3
Marked
Mark
A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Abstract:
In this paper we propose novel, audio-visual analysis techniques for event detection in broadcast TV sports video content. The scope of the design is constrained to the specialized domain of 'field sport', and specifically, Gaelic Football is presented as an experimental case study. We show that a combination of speech-band energy tracking in the audio domain, coupled with colour dominance pattern recognition in the video domain, provides a useful contribution to event detection for broadcast Gaelic Football matches. It is projected that, any conclusions made therein may be extended such that they function on sports content of a similar nature such as American Football, Australian Rules, Rugby Union etc.
http://doras.dcu.ie/244/
Marked
Mark
A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Abstract:
In this paper we propose a novel audio-visual feature-based framework, for event detection in field sports broadcast video. The system is evaluated via a case-study involving MPEG encoded soccer video. Specifically, the evidence gathered by various feature detectors is combined by means of a learning algorithm (a support vector machine), which infers the occurrence of an event, based on a model generated during a training phase, utilizing a corpus of 25 hours of content. The system is evaluated using 25 hours of separate test content. Following an evaluation of results obtained, it is shown for this case, that both high precision and recall statistics are achievable.
http://doras.dcu.ie/399/
Marked
Mark
A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
Abstract:
The paper presents an approach to segmenting broadcast TV news programmes automatically into individual news stories. We first segment the programme into individual shots, and then a number of analysis tools are run on the programme to extract features to represent each shot. The results of these feature extraction tools are then combined using a support vector machine trained to detect anchorperson shots. A news broadcast can then be segmented into individual stories based on the location of the anchorperson shots within the programme. We use one generic system to segment programmes from two different broadcasters, illustrating the robustness of our feature extraction process to the production styles of different broadcasters.
http://doras.dcu.ie/242/
Marked
Mark
An automatic technique for visual quality classification for MPEG-1 video
(2001)
Sav, Sorin Vasile; Marlow, Seán; Murphy, Noel; O'Connor, Noel E.
An automatic technique for visual quality classification for MPEG-1 video
(2001)
Sav, Sorin Vasile; Marlow, Seán; Murphy, Noel; O'Connor, Noel E.
Abstract:
The Centre for Digital Video Processing at Dublin City University developed Fischlar [1], a web-based system for recording, analysis, browsing and playback of digitally captured television programs. One major issue for Fischlar is the automatic evaluation of video quality in order to avoid processing and storage of corrupted data. In this paper we propose an automatic classification technique that detects the video content quality in order to provide a decision criterion for the processing and storage stages.
http://doras.dcu.ie/331/
Marked
Mark
An evaluation of alternative techniques for automatic detection of shot boundaries in digital video
(1999)
Smeaton, Alan F.; Gilvarry, J.; Gormley, G.; Tobin, B.; Marlow, Seán; Murphy, Noel
An evaluation of alternative techniques for automatic detection of shot boundaries in digital video
(1999)
Smeaton, Alan F.; Gilvarry, J.; Gormley, G.; Tobin, B.; Marlow, Seán; Murphy, Noel
Abstract:
The application of image processing techniques to achieve substantial compression in digital video is one of the reasons why computer-supported video processing and digital TV are now becoming commonplace. The encoding formats used for video, such as the MPEG family of standards, have been developed primarily to achieve high compression rates, but now that this has been achieved, effort is being concentrated on other, content-based activities. MPEG-7, for example is a standard intended to support such developments. In the work described here, we are developing and deploying techniques to support content-based navigation and browsing through digital video (broadcast TV) archives. Fundamental to this is being able to automatically structure video into shots and scenes. In this paper we report our progress on developing a variety of approaches to automatic shot boundary detection in MPEG-1 video, and their evaluation on a large test suite of 8 hours of broadcast TV. Our work to date i...
http://doras.dcu.ie/337/
Marked
Mark
An experiment in audio classification from compressed data
(2004)
Jarina, Roman; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
An experiment in audio classification from compressed data
(2004)
Jarina, Roman; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Abstract:
In this paper we present an algorithm for automatic classification of sound into speech, instrumental sound/ music and silence. The method is based on thresholding of features derived from the modulation envelope of the frequency limited audio signal. Four characteristics are examined for discrimination: the occurrence and duration of energy peaks, rhythmic content and the level of harmonic content. The proposed algorithm allows classification directly on MPEG-1 audio bitstreams. The performance of the classifier was evaluated on TRECVID test data. The test results are above-average among all TREC participants. The approaches adopted by other research groups participating in TREC are also discussed.
http://doras.dcu.ie/395/
Marked
Mark
An integrated approach for object shape registration and modeling
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Jones, Gareth J.F.; Murphy, Noel
An integrated approach for object shape registration and modeling
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Jones, Gareth J.F.; Murphy, Noel
Abstract:
In this paper, an integrated approach to fast and efficient construction of statistical shape models is proposed that is a potentially useful tool in Information Retrieval(IR). The tool allows intuitive extraction of accurate contour examples from a set of images using a semi-automatic segmentation approach. The user is allowed to draw on the scene by simply dragging a mouse over the image and creating a set of labelled scribbles for the objects to be segmented. An automatic segmentation algorithm uses the scribbles to partition the scene and extract objects’ contour. A set of labelled points (landmarks) is identified automatically on the set of examples thereby allowing statistical modeling of the objects’ shape. The main contribution of this paper is the new approach to automatic landmark identification eliminating the burden of manual landmarking. The approach utilizes a robust method for pairwise correspondence proposed originally in [1, 2]. The landmarks are used to train stati...
http://doras.dcu.ie/384/
Marked
Mark
Associating low-level features with semantic concepts using video objects and relevance feedback
(2005)
Sav, Sorin Vasile; O'Connor, Noel E.; Smeaton, Alan F.; Murphy, Noel
Associating low-level features with semantic concepts using video objects and relevance feedback
(2005)
Sav, Sorin Vasile; O'Connor, Noel E.; Smeaton, Alan F.; Murphy, Noel
Abstract:
The holy grail of multimedia indexing and retrieval is developing algorithms capable of imitating human abilities in distinguishing and recognising semantic concepts within the content, so that retrieval can be based on ”real world” concepts that come naturally to users. In this paper, we discuss an approach to using segmented video objects as the midlevel connection between low-level features and semantic concept description. In this paper, we consider a video object as a particular instance of a semantic concept and we model the semantic concept as an average representation of its instances. A system supporting object-based search through a test corpus is presented that allows matching presegmented objects based on automatically extracted lowlevel features. In the system, relevance feedback is employed to drive the learning of the semantic model during a regular search process.
http://doras.dcu.ie/403/
Marked
Mark
Audio and video processing for automatic TV advertisement detection
(2001)
Marlow, Seán; Sadlier, David A.; McGeough, Karen; O'Connor, Noel E.; Murphy, Noel
Audio and video processing for automatic TV advertisement detection
(2001)
Marlow, Seán; Sadlier, David A.; McGeough, Karen; O'Connor, Noel E.; Murphy, Noel
Abstract:
As a partner in the Centre for Digital Video Processing, the Visual Media Processing Group at Dublin City University conducts research and development in the area of digital video management. The current stage of development is demonstrated on our Web-based digital video system called Físchlár [1,2], which provides for efficient recording, analyzing, browsing and viewing of digitally captured television programmes. In order to make the browsing of programme material more efficient, users have requested the option of automatically deleting advertisement breaks. Our initial work on this task focused on locating ad-breaks by detecting patterns of silent black frames which separate individual advertisements and/or complete ad-breaks in most commercial TV stations. However, not all TV stations use silent, black frames to flag ad-breaks. We therefore decided to attempt to detect advertisements using the rate of shot cuts in the digitised TV signal. This paper describes the implementation ...
http://doras.dcu.ie/334/
Marked
Mark
Audio processing for automatic TV sports program highlights detection
(2002)
Marlow, Seán; Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel
Audio processing for automatic TV sports program highlights detection
(2002)
Marlow, Seán; Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel
Abstract:
In today’s fast paced world, the time available to watch long sports programmes is decreasing, while the number of sports channels is rapidly increasing. Many viewers desire the facility to watch just the highlights of sports events. This paper presents a simple, but effective, method for generating sports video highlights summaries. Our method detects semantically important events in sports programmes by using the Scale Factors in the MPEG audio bitstream to generate an audio amplitude profile of the program. The Scale Factors for the subbands corresponding to the voice bandwidth give a strong indication of the level of commentator and/or spectator excitement. When periods of sustained high audio amplitude have been detected and ranked, the corresponding video shots may be concatenated to produce a summary of the program highlights. Our method uses only the Scale Factor information that is directly accessible from the MPEG bitstream, without any decoding, leading to highly efficien...
http://doras.dcu.ie/326/
Marked
Mark
Automatic detection and extraction of artificial text in video
(2004)
Malobabić, Jovanka; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Automatic detection and extraction of artificial text in video
(2004)
Malobabić, Jovanka; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Abstract:
A significant challenge in large multimedia databases is the provision of efficient means for semantic indexing and retrieval of visual information. Artificial text in video is normally generated in order to supplement or summarise the visual content and thus is an important carrier of information that is highly relevant to the content of the video. As such, it is a potential ready-to-use source of semantic information. In this paper we present an algorithm for detection and localisation of artificial text in video using a horizontal difference magnitude measure and morphological processing. The result of character segmentation, based on a modified version of the Wolf-Jolion algorithm [1][2] is enhanced using smoothing and multiple binarisation. The output text is input to an “off-the-shelf” noncommercial OCR. Detection, localisation and recognition results for a 20min long MPEG-1 encoded television programme are presented.
http://doras.dcu.ie/421/
Marked
Mark
Automatic TV advertisement detection from MPEG bitstream
(2002)
Sadlier, David A.; Marlow, Seán; O'Connor, Noel E.; Murphy, Noel
Automatic TV advertisement detection from MPEG bitstream
(2002)
Sadlier, David A.; Marlow, Seán; O'Connor, Noel E.; Murphy, Noel
Abstract:
The Centre for Digital Video Processing at Dublin City University conducts concentrated research and development in the area of digital video management. The current stage of development is demonstrated on our Web-based digital video system called Físchlár (Proceedings of the Content based Multimedia Information Access, RIAO 2000, Vol. 2, Paris, France, 12–14 April 2000, p. 1390), which provides for efficient recording, analysing, browsing and viewing of digitally captured television programmes. Advertisement breaks during or between television programmes are typically recognised by a series of ‘black’ video frames simultaneously accompanying a depression in audio volume which separate each advertisement from one another by recurrently occurring before and after each individual advertisement. It is the regular prevalence of these flags that enables automatic differentiation between what is programme and what is a commercial break. This paper reports on the progress made in the deve...
http://doras.dcu.ie/385/
Marked
Mark
Automatically detecting camera motion from MPEG-1 encoded video
(2000)
Donnelly, Stephen; Smeaton, Alan F.; Berrut, Catherine; Marlow, Seán; Murphy, Noel; O...
Automatically detecting camera motion from MPEG-1 encoded video
(2000)
Donnelly, Stephen; Smeaton, Alan F.; Berrut, Catherine; Marlow, Seán; Murphy, Noel; O'Connor, Noel E.
http://doras.dcu.ie/335/
Marked
Mark
Background modelling in infrared and visible spectrum video for people tracking
(2005)
Ó Conaire, Ciarán; Cooke, Eddie; O'Connor, Noel E.; Murphy, Noel; Smeaton, Alan F.
Background modelling in infrared and visible spectrum video for people tracking
(2005)
Ó Conaire, Ciarán; Cooke, Eddie; O'Connor, Noel E.; Murphy, Noel; Smeaton, Alan F.
Abstract:
In this paper, we present our approach to robust background modelling which combines visible and thermal infrared spectrum data. Our work is based on the non-parametric background model describe in 1. We use a pedestrian detection module to prevent erroneous data from becoming part of the background model and this allows us to initialise our bacjground model, even in the presence of foreground objects. Visible and infrared features are use to remove incorrectly detected foreground regions. Allowing our model to quickly recover from ghost regions and rapid lighting changes. An object-based shadow detector also improves our algorithm's performance.
http://doras.dcu.ie/240/
Marked
Mark
Detecting the presence of large buildings in natural images
(2005)
Malobabić, Jovanka; Le Borgne, Hervé; Murphy, Noel; O'Connor, Noel E.
Detecting the presence of large buildings in natural images
(2005)
Malobabić, Jovanka; Le Borgne, Hervé; Murphy, Noel; O'Connor, Noel E.
Abstract:
This paper addresses the issue of classification of lowlevel features into high-level semantic concepts for the purpose of semantic annotation of consumer photographs. We adopt a multi-scale approach that relies on edge detection to extract an edge orientation-based feature description of the image, and apply an SVM learning technique to infer the presence of a dominant building object in a general purpose collection of digital photographs. The approach exploits prior knowledge on the image context through an assumption that all input images are �outdoor�, i.e. indoor/outdoor classification (the context determination stage) has been performed. The proposed approach is validated on a diverse dataset of 1720 images and its performance compared with that of the MPEG-7 edge histogram descriptor.
http://doras.dcu.ie/444/
Marked
Mark
Dialogue scene detection in movies using low and mid-level visual features
(2004)
Lehane, Bart; O'Connor, Noel E.; Murphy, Noel
Dialogue scene detection in movies using low and mid-level visual features
(2004)
Lehane, Bart; O'Connor, Noel E.; Murphy, Noel
Abstract:
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.
http://doras.dcu.ie/400/
Marked
Mark
Dublin City University video track experiments for TREC 2002
(2002)
Browne, Paul; Czirjék, Csaba; Gurrin, Cathal; Jarina, Roman; Lee, Hyowon; Marlow, Seán;...
Dublin City University video track experiments for TREC 2002
(2002)
Browne, Paul; Czirjék, Csaba; Gurrin, Cathal; Jarina, Roman; Lee, Hyowon; Marlow, Seán; McDonald, Kieran; Murphy, Noel; O'Connor, Noel E.; Smeaton, Alan F.; Ye, Jiamin
Abstract:
Dublin City University participated in the Feature Extraction task and the Search task of the TREC-2002 Video Track. In the Feature Extraction task, we submitted 3 features: Face, Speech, and Music. In the Search task, we developed an interactive video retrieval system, which incorporated the 40 hours of the video search test collection and supported user searching using our own feature extraction data along with the donated feature data and ASR transcript from other Video Track groups. This video retrieval system allows a user to specify a query based on the 10 features and ASR transcript, and the query result is a ranked list of videos that can be further browsed at the shot level. To evaluate the usefulness of the feature-based query, we have developed a second system interface that provides only ASR transcript-based querying, and we conducted an experiment with 12 test users to compare these 2 systems. Results were submitted to NIST and we are currently conducting further analys...
http://doras.dcu.ie/323/
Marked
Mark
Dublin City University video track experiments for TREC 2003
(2003)
Browne, Paul; Czirjék, Csaba; Gaughan, Georgina; Gurrin, Cathal; Jones, Gareth J.F.; Le...
Dublin City University video track experiments for TREC 2003
(2003)
Browne, Paul; Czirjék, Csaba; Gaughan, Georgina; Gurrin, Cathal; Jones, Gareth J.F.; Lee, Hyowon; Marlow, Seán; McDonald, Kieran; Murphy, Noel; O'Connor, Noel E.; O'Hare, Neil; Smeaton, Alan F.; Ye, Jiamin
Abstract:
In this paper, we describe our experiments for both the News Story Segmentation task and Interactive Search task for TRECVID 2003. Our News Story Segmentation task involved the use of a Support Vector Machine (SVM) to combine evidence from audio-visual analysis tools in order to generate a listing of news stories from a given news programme. Our Search task experiment compared a video retrieval system based on text, image and relevance feedback with a text-only video retrieval system in order to identify which was more effective. In order to do so we developed two variations of our Físchlár video retrieval system and conducted user testing in a controlled lab environment. In this paper we outline our work on both of these two tasks.
http://doras.dcu.ie/434/
Marked
Mark
Engagement and Learning from a team-based mini-project in mechatronic engineering
(2020)
Murphy, Noel; Bruton, Jennifer
Engagement and Learning from a team-based mini-project in mechatronic engineering
(2020)
Murphy, Noel; Bruton, Jennifer
Abstract:
We outline our experiences with hidden and unsignposted learning by us and by our students arising from a team-based project activity in a 3rd-year undergraduate engineering module in the general Mechatronics area. We discuss the hidden learning achieved in areas such as team communications, team management, problem-solving skills, and communication through the media of student-produced video and presentations, as well as technical engineering reports. We describe the enablement of student reflection on their learning and its benefits and use these reflections to evidence various aspects of their learning. The work is situated within the literature on innovations and quality of STEM education.
http://doras.dcu.ie/24932/
Marked
Mark
Evaluating and combining digital video shot boundary detection algorithms
(2000)
Browne, Paul; Smeaton, Alan F.; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán; Ber...
Evaluating and combining digital video shot boundary detection algorithms
(2000)
Browne, Paul; Smeaton, Alan F.; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán; Berrut, Catherine
Abstract:
The development of standards for video encoding coupled with the increased power of computing mean that content-based manipulation of digital video information is now feasible. Shots are a basic structural building block of digital video and the boundaries between shots need to be determined automatically to allow for content-based manipulation. A shot can be thought of as continuous images from one camera at a time. In this paper we examine a variety of automatic techniques for shot boundary detection that we have implemented and evaluated on a baseline of 720,000 frames (8 hours) of broadcast television. This extends our previous work on evaluating a single technique based on comparing colour histograms. A description of each of our three methods currently working is given along with how they are evaluated. It is found that although the different methods have about the same order of magnitude in terms of effectiveness, different shot boundaries are detected by the different method...
http://doras.dcu.ie/336/
Marked
Mark
Evaluation of automatic shot boundary detection on a large video test suite
(1999)
O'Toole, Colin; Smeaton, Alan F.; Murphy, Noel; Marlow, Seán
Evaluation of automatic shot boundary detection on a large video test suite
(1999)
O'Toole, Colin; Smeaton, Alan F.; Murphy, Noel; Marlow, Seán
Abstract:
The challenge facing the indexing of digital video information in order to support browsing and retrieval by users, is to design systems that can accurately and automatically process large amounts of heterogeneous video. The segmentation of video material into shots and scenes is the basic operation in the analysis of video content. This paper presents a detailed evaluation of a histogram-based shot cut detector based on eight hours of TV broadcast video. Our observations are that the selection of similarity thresholds for determining shot boundaries in such broadcast video is difficult and necessitates the development of systems that employ adaptive thresholding in order to address the huge variation of characteristics prevalent in TV broadcast video.
http://doras.dcu.ie/346/
Marked
Mark
Experiments in terabyte searching, genomic retrieval and novelty detection for TREC 2004
(2004)
Blott, Stephen; Boydell, Oisín; Camous, Fabrice; Ferguson, Paul; Gaughan, Georgina; Gur...
Experiments in terabyte searching, genomic retrieval and novelty detection for TREC 2004
(2004)
Blott, Stephen; Boydell, Oisín; Camous, Fabrice; Ferguson, Paul; Gaughan, Georgina; Gurrin, Cathal; Jones, Gareth J.F.; Murphy, Noel; O'Connor, Noel E.; Smeaton, Alan F.; Smyth, Barry; Wilkins, Peter
Abstract:
In TREC2004, Dublin City University took part in three tracks, Terabyte (in collaboration with University College Dublin), Genomic and Novelty. In this paper we will discuss each track separately and present separate conclusions from this work. In addition, we present a general description of a text retrieval engine that we have developed in the last year to support our experiments into large scale, distributed information retrieval, which underlies all of the track experiments described in this document.
http://doras.dcu.ie/318/
Marked
Mark
Face detection and clustering for video indexing applications
(2003)
Czirjék, Csaba; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Face detection and clustering for video indexing applications
(2003)
Czirjék, Csaba; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Abstract:
This paper describes a method for automatically detecting human faces in generic video sequences. We employ an iterative algorithm in order to give a confidence measure for the presence or absence of faces within video shots. Skin colour filtering is carried out on a selected number of frames per video shot, followed by the application of shape and size heuristics. Finally, the remaining candidate regions are normalized and projected into an eigenspace, the reconstruction error being the measure of confidence for presence/absence of face. Following this, the confidence score for the entire video shot is calculated. In order to cluster extracted faces into a set of face classes, we employ an incremental procedure using a PCA-based dissimilarity measure in con-junction with spatio-temporal correlation. Experiments were carried out on a representative broadcast news test corpus.
http://doras.dcu.ie/341/
Marked
Mark
Físchlár on a PDA: handheld user interface design to a video indexing, browsing and playback system
(2001)
Lee, Hyowon; Smeaton, Alan F.; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán
Físchlár on a PDA: handheld user interface design to a video indexing, browsing and playback system
(2001)
Lee, Hyowon; Smeaton, Alan F.; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán
Abstract:
The Físchlár digital video system is a web-based system for recording, analysis, browsing and playback of TV programmes which currently has about 350 users. Although the user interface to the system is designed for desktop PCs with a large screen and a mouse, we are developing versions to allow the use of mobile devices to access the system to record and browse the video content. In this paper, the design of a PDA user interface to video content browsing is considered. We use a design framework we have developed previously to be able to specify various video browsing interface styles thus making it possible to design for all potential users and their various environments. We can then apply this to the particulars of the PDA's small, touch-sensitive screen and the mobile environment where it will be used. The resultant video browsing interfaces have highly interactive interfaces yet are simple, which requires relatively less visual attention and focusing, and can be comfortably ...
http://doras.dcu.ie/333/
Marked
Mark
Físchlár: an on-line system for indexing and browsing broadcast television content
(2001)
O'Connor, Noel E.; Marlow, Seán; Murphy, Noel; Smeaton, Alan F.; Browne, Paul; Dea...
Físchlár: an on-line system for indexing and browsing broadcast television content
(2001)
O'Connor, Noel E.; Marlow, Seán; Murphy, Noel; Smeaton, Alan F.; Browne, Paul; Deasy, Seán; Lee, Hyowon; McDonald, Kieran
Abstract:
This paper describes a demonstration system which automatically indexes broadcast television content for subsequent non-linear browsing. User-specified television programmes are captured in MPEG-1 format and analysed using a number of video indexing tools such as shot boundary detection, keyframe extraction, shot clustering and news story segmentation. A number of different interfaces have been developed which allow a user to browse the visual index created by these analysis tools. These interfaces are designed to facilitate users locating video content of particular interest. Once such content is located, the MPEG-1 bitstream can be streamed to the user in real-time. This paper describes both the high-level functionality of the system and the low-level indexing tools employed, as well as giving an overview of the different browsing mechanisms employed
http://doras.dcu.ie/249/
Displaying Results 1 - 25 of 56 on page 1 of 3
1
2
3
Bibtex
CSV
EndNote
RefWorks
RIS
XML
Year
2020 (1)
2019 (1)
2007 (1)
2005 (12)
2004 (9)
2003 (9)
2002 (7)
2001 (9)
2000 (4)
1999 (2)
1992 (1)
built by Enovation Solutions