What do we mean by the term "inflammation"? A contemporary basic science update for sports medicine

Most practicing sports medicine clinicians refer to the concept of "inflammation" many times a day when diagnosing and treating acute and overuse injuries. What is meant by this term? Is it a "good" or a "bad" process? The major advances in the understanding of inflammation in recent years are summarised, and some clinical implications of the contemporary model of inflammation are highlighted.

Prevalence of health promotion policies in sports clubs in Victoria, Australia

In recent years, some health agencies offered sponsorship to sporting associations to promote healthy environments by encouraging clubs to develop health-related policies. However, the extent to which these sponsorship contracts reach their stated aims is of concern. This study aimed to quantify levels of policy development and practice in sports clubs for each of five key health areas, namely smoke-free facilities, sun protection, healthy catering, responsible serving of alcohol and sports injury prevention. Representatives from 932 Victorian sports clubs were contacted by telephone with 640 clubs (69%) participating in the survey. Results suggested that the establishment of written policies on the key health areas by sports clubs varied widely by affiliated sport and health area: 70% of all clubs with bar facilities had written policies on responsible serving of alcohol, ranging from 58% of tennis clubs to 100% of diving and surfing clubs. In contrast, approximately one-third of sports clubs had a smoke-free policy, with 36% of tennis, 28% of country football and 28% of men's cricket clubs having policy. Moreover, 34% of clubs overall had established sun protection policy, whereas clubs competing outside during summer months, [diving (86%) and life-saving (81%)] were most likely to have a written sun protection policy. Injury prevention policies were established in 30% of sports clubs, and were most common among football (56%), diving (43%) and life-saving (41%). This study suggests that policy development for health promotion can be achieved in sports clubs when it is well supported by health agencies and consideration is given to the appropriateness of the specific behaviours to be encouraged for a given sport. Communication between associations and clubs needs to be monitored by health agencies to ensure support and resources for policy development to reach the club level.

Sports events and the female market : an investigation of attendance motivations

Over the last five years, attendance at sports events in Australia has grown at a rate of 13%; however, male spectators outnumber female spectators by 25% (ABS 2003). Drawing on a sample of 175 female respondents from the city and suburbs of Melbourne, this study identifies and explores the factors that motivate their attendance at sports events. The results show that social dimensions as well as on site entertainment can have a strong influence in attracting a female audience and that omen will
not attend if the facilities provided are not of a high standard.

Towards universal and statistical-driven heuristics for automatic classification of sports video events

Researchers worldwide have been actively seeking for the most robust and powerful solutions to detect and classify key events (or highlights) in various sports domains. Most approaches have employed manual heuristics that model the typical pattern of audio-visual features within particular sport events To avoid manual observation and knowledge, machine-learning can be used as an alternative approach. To bridge the gaps between these two alternatives, an attempt is made to integrate statistics into heuristic models during highlight detection in our investigation. The models can be designed with a modest amount of domain-knowledge, making them less subjective and more robust for different sports. We have also successfully used a universal scope of detection and a standard set of features that can be applied for different sports that include soccer, basketball and Australian football. An experiment on a large dataset of sport videos, with a total of around 15 hours, has demonstrated the effectiveness and robustness of our
aIlgorithms.

Extensible detection and indexing of highlight events in broadcasted sports video

Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sports video. The main challenge is to design extensible frameworks to detect and index highlight events. This paper presents: 1) A statistical-driven event detection approach that utilizes a minimum amount of manual knowledge and is based on a universal scope-of-detection and audio-visual features; 2) A semi-schema-based indexing that combines the benefits of schema-based modeling to ensure that the video indexes are valid at all time without manual checking, and schema-less modeling to allow several passes of instantiation in which additional elements can be declared. To demonstrate the performance of the events detection, a large dataset of sport videos with a total of around 15 hours including soccer, basketball and Australian football is used.

Using decision-tree to automatically construct learned-heuristics for events classification in sports video

Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.