Event detection based on generic characteristics of field-sports

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

Event detection in field sports video using audio-visual features and a support vector machine

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

Maternal depression and youth internalizing and externalizing symptomatology: severity and chronicity of past maternal depression and current maternal depressive symptoms

Maternal depression is a well-documented risk factor for youth depression, and taking into account its severity and chronicity may provide important insight into the degree of risk conferred. This study explored the degree to which the severity/chronicity of maternal depression history explained variance in youth internalizing and externalizing symptoms above and beyond current maternal depressive symptoms among 171 youth (58 % male) ages 8 to 12 over a span of 3 years. Severity and chronicity of past maternal depression and current maternal depressive symptoms were examined as predictors of parent-reported youth internalizing and externalizing symptomatology, as well as youth self-reported depressive symptoms. Severity and chronicity of past maternal depression did not account for additional variance in youth internalizing and externalizing symptoms at Time 1 beyond what was accounted for by maternal depressive symptoms at Time 1. Longitudinal growth curve modeling indicated that prior severity/chronicity of maternal depression predicted levels of youth internalizing and externalizing symptoms at each time point when controlling for current maternal depressive symptoms at each time point. Chronicity of maternal depression, apart from severity, also predicted rate of change in youth externalizing symptoms over time. These findings highlight the importance of screening and assessing for current maternal depressive symptoms, as well as the nature of past depressive episodes. Possible mechanisms underlying the association between severity/chronicity of maternal depression and youth outcomes, such as residual effects from depressive history on mother–child interactions, are discussed.The current work was supported by grants from the National Institutes of Health (MH066077, PI: Martha C. Tompson, PhD; MH082861, PI: Martha C. Tompson, PhD;). (MH066077 - National Institutes of Health; MH082861 - National Institutes of Health)Published versio

Where are the veterinarian shortage areas anyway?

This paper describes an econometric model to evaluate factors associated with a county’s likelihood of being designated as a private practice shortage area under the United States' Veterinary Medicine Loan Repayment Program (VMLRP). Study determinants of equilibrium food animal veterinarian location choices were also evaluated and used as a benchmark to assess the shortage designation process. On the whole the program appears to perform quite well. For several states, however, VMLRP shortage designations are inconsistent with the model of food animal veterinarian shortages. Comparative shortage is generally more severe in states that have no VMLRP designated private practice shortage counties than in states that do.economic externalities, food animal veterinarians, loan repayment program, Agricultural and Food Policy, Livestock Production/Industries,

A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video

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

Audio processing for automatic TV sports program highlights detection

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 efficient computation. It is also rather more generic than many existing techniques, being particularly suitable for the more popular sports televised in Ireland such as soccer, Gaelic football, hurling, rugby, horse racing and motor racing

InSPeCT: Integrated Surveillance for Port Container Traffic

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

Audio and video processing for automatic TV advertisement detection

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 and performance of both methods of ad-break detection

A content-based retrieval system for UAV-like video and associated metadata

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' trips with additional information. Interaction with the CBR system is via a novel interactive map-based interface. This interface supports content access by time, date, region of interest on the map, previously annotated specific locations of interest and combinations of these. To develop such a system and investigate its practical usefulness in real world scenarios, clearly a significant amount of appropriate data is required. In the absence of a large volume of UAV data with which to work, we have simulated UAV-like data using GPS tagged video content captured from moving vehicles