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Author = Sadlier, David A.;
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Displaying Results 1 - 18 of 18 on page 1 of 1
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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/
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A content-based retrieval system for UAV-like video and associated metadata
(2008)
O'Connor, Noel E.; Duffy, Thomas; Gurrin, Cathal; Lee, Hyowon; Sadlier, David A.; ...
A content-based retrieval system for UAV-like video and associated metadata
(2008)
O'Connor, Noel E.; Duffy, Thomas; Gurrin, Cathal; Lee, Hyowon; Sadlier, David A.; Smeaton, Alan F.; Zhang, Ke
Abstract:
In this paper we provide an overview of a content-based retrieval (CBR) system that has been specifically designed for handling UAV video and associated meta-data. Our emphasis in designing this system is on managing large quantities of such information and providing intuitive and efficient access mechanisms to this content, rather than on analysis of the video content. The retrieval unit in our system is termed a "trip". At capture time, each trip consists of an MPEG-1 video stream and a set of time stamped GPS locations. An analysis process automatically selects and associates GPS locations with the video timeline. The indexed trip is then stored in a shared trip repository. The repository forms the backend of a MPEG-211 compliant Web 2.0 application for subsequent querying, browsing, annotation and video playback. The system interface allows users to search/browse across the entire archive of trips and, depending on their access rights, to annotate other users' tri...
http://doras.dcu.ie/2449/
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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/
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An architecture for mining resources complementary to audio-visual streams
(2007)
Nemrava, Jan; Buitelaar, Paul; Declerck, Thierry; Svátek, Vojtech; Petrák, Josef; Cobet...
An architecture for mining resources complementary to audio-visual streams
(2007)
Nemrava, Jan; Buitelaar, Paul; Declerck, Thierry; Svátek, Vojtech; Petrák, Josef; Cobet, Andreas; Zeiner, Herwig; Sadlier, David A.; O'Connor, Noel E.; Simou, Nikos; Tzouvaras, Vassilis
Abstract:
In this paper we attempt to characterize resources of information complementary to audio-visual (A/V) streams and propose their usage for enriching A/V data with semantic concepts in order to bridge the gap between low-level video detectors and high-level analysis. Our aim is to extract cross-media feature descriptors from semantically enriched and aligned resources so as to detect finer-grained events in video.We introduce an architecture for complementary resource analysis and discuss domain dependency aspects of this approach related to our domain of soccer broadcasts.
http://doras.dcu.ie/387/
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Architecture for enhancing video analysis results using complementary resources
(2007)
Nemrava, Jan; Buitelaar, Paul; Declerck, Thierry; Svátek, Vojtech; Petrák, Josef; Cobet...
Architecture for enhancing video analysis results using complementary resources
(2007)
Nemrava, Jan; Buitelaar, Paul; Declerck, Thierry; Svátek, Vojtech; Petrák, Josef; Cobet, Andreas; Zeiner, Herwig; Sadlier, David A.; O'Connor, Noel E.
Abstract:
In this paper we present different sources of information complementary to audio-visual (A/V) streams and propose their usage for enriching A/V data with semantic concepts in order to bridge the gap between low-level video analysis and high-level analysis. Our aim is to extract cross-media feature descriptors from semantically enriched and aligned resources so as to detect finer-grained events in video. We introduce an architecture for complementary resources analysis and discuss domain dependency aspects of this approach connected to our initial domain of soccer broadcasts.
http://doras.dcu.ie/306/
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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/
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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/
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Audio/visual analysis for high-speed TV advertisement detection from MPEG bitstream
(2002)
Sadlier, David A.
Audio/visual analysis for high-speed TV advertisement detection from MPEG bitstream
(2002)
Sadlier, David A.
Abstract:
Advertisement breaks dunng or between television programmes are typically flagged by senes of black-and-silent video frames, which recurrendy occur in order to audio-visually separate individual advertisement spots from one another. It is the regular prevalence of these flags that enables automatic differentiauon between what is programme content and what is advertisement break. Detection of these audio-visual depressions within broadcast television content provides a basis on which advertisement detection may be achieved. This document reports on the progress made in the development of this idea into an advertisement detector system that automatically detects the advertisement breaks direcdy from the MPEG-1 encoded bitstream of digitally captured television broadcasts.
http://doras.dcu.ie/18205/
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Audiovisual processing for sports-video summarisation technology
(2006)
Sadlier, David A.
Audiovisual processing for sports-video summarisation technology
(2006)
Sadlier, David A.
Abstract:
In this thesis a novel audiovisual feature-based scheme is proposed for the automatic summarization of sports-video content The scope of operability of the scheme is designed to encompass the wide variety o f sports genres that come under the description ‘field-sports’. Given the assumption that, in terms of conveying the narrative of a field-sports-video, score-update events constitute the most significant moments, it is proposed that their detection should thus yield a favourable summarisation solution. To this end, a generic methodology is proposed for the automatic identification of score-update events in field-sports-video content. The scheme is based on the development of robust extractors for a set of critical features, which are shown to reliably indicate their locations. The evidence gathered by the feature extractors is combined and analysed using a Support Vector Machine (SVM), which performs the event detection process. An SVM is chosen on the basis that its underlying t...
http://doras.dcu.ie/18207/
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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/
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Event detection based on generic characteristics of field-sports
(2005)
Sadlier, David A.; O'Connor, Noel E.
Event detection based on generic characteristics of field-sports
(2005)
Sadlier, David A.; O'Connor, Noel E.
Abstract:
In this paper, we propose a generic framework for event detection in broadcast video of multiple different field-sports. Features indicating significant events are selected, and robust detectors built. These features are rooted in generic characteristics common to all genres of field-sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested across multiple genres of field-sports including soccer, rugby, hockey and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable.
http://doras.dcu.ie/239/
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Event detection in field sports video using audio-visual features and a support vector machine
(2005)
Sadlier, David A.; O'Connor, Noel E.
Event detection in field sports video using audio-visual features and a support vector machine
(2005)
Sadlier, David A.; O'Connor, Noel E.
Abstract:
In this paper, we propose a novel audio-visual feature-based framework for event detection in broadcast video of multiple different field sports. Features indicating significant events are selected and robust detectors built. These features are rooted in characteristics common to all genres of field sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested generically across multiple genres of field sports including soccer, rugby, hockey, and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable.
http://doras.dcu.ie/254/
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Image-based vehicle indexing for a seaport transportation surveillance system
(2011)
Sadlier, David A.; Ferguson, Paul; Ó Conaire, Ciarán; O'Connor, Noel E.
Image-based vehicle indexing for a seaport transportation surveillance system
(2011)
Sadlier, David A.; Ferguson, Paul; Ó Conaire, Ciarán; O'Connor, Noel E.
Abstract:
In this paper we describe and evaluate two methods underpinning a surveillance-based content management system, designed for monitoring and profiling freight-based vehicular traffic in a seaport environment. The `InSPeCT' system captures video footage of passing vehicles, and uses tailored optical character recognition (OCR) to index the footage according to vehicle license-plates and freight codes. The system provides advanced search techniques for the efficient retrieval of records, where each captured vehicle is profiled according to captured imagery and its associated interpretations. Underpinning this system is a method for detecting the boundaries of individual transits within sustained traffic flow. Considering it desirable to extend the indexing functionality of the system beyond OCR, a colour-based vehicle indexing approach is proposed and evaluated. All evaluations take place in the context of a system deployed in a busy national seaport.
http://doras.dcu.ie/16355/
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InSPeCT: Integrated Surveillance for Port Container Traffic
(2011)
Sadlier, David A.; Ferguson, Paul; Zhang, Dian; O'Connor, Noel E.; Lee, Hyowon
InSPeCT: Integrated Surveillance for Port Container Traffic
(2011)
Sadlier, David A.; Ferguson, Paul; Zhang, Dian; O'Connor, Noel E.; Lee, Hyowon
Abstract:
This paper describes a fully-operational content-indexing and management system, designed for monitoring and profiling freight-based vehicular traffic in a seaport environment. The 'InSPeCT' system captures video footage of passing vehicles and uses tailored OCR to index the footage according to vehicle license plates and freight codes. In addition to real-time functionality such as alerting, the system provides advanced search techniques for the efficient retrieval of records, where each vehicle is profiled according to multi-angled video, context information, and links to external information sources. Currently being piloted at a busy national seaport, the feedback from port officials indicates the system to be extremely useful in supplementing their existing transportation-security structures.
http://doras.dcu.ie/16585/
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K-Space at TRECVid 2006
(2006)
Wilkins, Peter; Adamek, Tomasz; Ferguson, Paul; Hughes, Mark; Jones, Gareth J.F.; Keena...
K-Space at TRECVid 2006
(2006)
Wilkins, Peter; Adamek, Tomasz; Ferguson, Paul; Hughes, Mark; Jones, Gareth J.F.; Keenan, Gordon; McGuinness, Kevin; Malobabić, Jovanka; O'Connor, Noel E.; Sadlier, David A.; Smeaton, Alan F.
Abstract:
In this paper we describe the K-Space participation in TRECVid 2006. K-Space participated in two tasks, high-level feature extraction and search. We present our approaches for each of these activities and provide a brief analysis of our results. Our high-level feature submission made use of support vector machines (SVMs) created with low-level MPEG-7 visual features, fused with specific concept detectors. Search submissions were both manual and automatic and made use of both low- and high-level features. In the high-level feature extraction submission, four of our six runs achieved performance above the TRECVid median, whilst our search submission performed around the median. The K-Space team consisted of eight partner institutions from the EU-funded K-Space Network, and our submissions made use of tools and techniques from each partner. As such this paper will provide overviews of each partner’s contributions and provide appropriate references for specific descriptions of individua...
http://doras.dcu.ie/429/
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MPEG audio bitstream processing towards the automatic generation of sports programme summaries
(2003)
Sadlier, David A.; Marlow, Seán; O'Connor, Noel E.; Murphy, Noel
MPEG audio bitstream processing towards the automatic generation of sports programme summaries
(2003)
Sadlier, David A.; Marlow, Seán; O'Connor, Noel E.; Murphy, Noel
Abstract:
The frequency subband scale-factors are fundamental components of MPEG-1 audio encoded bitstreams. Examination of scale-factor weights is sufficient for the establishment of an audio amplitude profile of an audio track. If, for sports programme TV broadcasts, the audio amplitude is assumed to primarily reflect the noise level exhibited by the commentator (and/or attending spectators), then, this vocal reaction to the significance of unfolding events may be used as a basis for summarisation. i.e. by relying on the exhilaration, or otherwise, expressed by the commentator/spectators, individual clips of the programme (e.g. camera shots), may be ranked according to their relative significance. A summary may then be produced by amalgamating (chronologically) any number of these clips corresponding to selected audio peaks.
http://doras.dcu.ie/245/
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Semantic analysis of field sports video using a petri-net of audio-visual concepts
(2009)
Liang, Bai; Lao, Songyang; Smeaton, Alan F.; O'Connor, Noel E.; Sadlier, David A.;...
Semantic analysis of field sports video using a petri-net of audio-visual concepts
(2009)
Liang, Bai; Lao, Songyang; Smeaton, Alan F.; O'Connor, Noel E.; Sadlier, David A.; Sinclair, David
Abstract:
The most common approach to automatic summarisation and highlight detection in sports video is to train an automatic classifier to detect semantic highlights based on occurrences of low-level features such as action replays, excited commentators or changes in a scoreboard. We propose an alternative approach based on the detection of perception concepts (PCs) and the construction of Petri-Nets which can be used for both semantic description and event detection within sports videos. Low-level algorithms for the detection of perception concepts using visual, aural and motion characteristics are proposed, and a series of Petri-Nets composed of perception concepts is formally defined to describe video content. We call this a Perception Concept Network-Petri Net (PCN-PN) model. Using PCN-PNs, personalized high-level semantic descriptions of video highlights can be facilitated and queries on high-level semantics can be achieved. A particular strength of this framework is that we can ...
http://doras.dcu.ie/15013/
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Voice processing for automatic TV sports program highlights detection
(2003)
Marlow, Seán; Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel
Voice processing for automatic TV sports program highlights detection
(2003)
Marlow, Seán; Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel
Abstract:
The imminent rapid expansion in the number of TV channels is driving the need for efficient digital video indexing, browsing and playback systems. For the past four years, the Centre for Digital Video Processing in DCU has been working towards the provision of such a system. The current stage of development is demonstrated on our Web-based digital video system called Físchlár [1,2], which is now in hourly use by over 1000 registered users. At present a user can pre-set the recording of TV broadcast programmes and can choose from a set of different browser interfaces which allow navigation through the recorded programmes. As our research has developed we have been adding increased functionality such as personalisation and programme recommendation, automatic recording, SMS/WAP/PDA alerting, searching, summarising and so on. There have been many approaches to automatic highlight detection and summarization of sports programmes [3-6]. However, most methods are oriented to particular spo...
http://doras.dcu.ie/321/
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