322,253 research outputs found
Is a Dominant Service-Centric Sector Good for Diversity of Provision?
Get PDFAn obvious assumption underpinning the immense interest in service-oriented computing is that it is an inherently Good Thing, by which we mean that robust processes and tools for developing service-based systems will bring benefits for service providers and service consumers. The arguments, in terms of consumer choice and flexibility, are certainly quite convincing. However, in this position paper, we question the nature of the underlying assumption, in a world where requirements are as many and varied as potential users and ask if safeguards are needed to ensure that diversity of provision is maintained
A query description model based on basic semantic unit composite Petri-Net for soccer video
Get PDFDigital video networks are making available increasing amounts of sports video data. The volume of material on offer means that sports fans often rely on prepared summaries of game highlights to follow the progress of their favourite teams. A significant application area for automated video analysis technology is the generation of personalized highlights of sports events. One of the most popular sports around world is soccer. A soccer game is composed of a range of significant events, such as goal scoring, fouls, and substitutions. Automatically detecting these events in a soccer video can enable users to interactively design their own highlights programmes. From an analysis of broadcast soccer video, we propose a query description model based on Basic Semantic Unit Composite Petri-Nets (BSUCPN) to automatically detect significant events within soccer video. Firstly we define a Basic Semantic Unit (BSU) set for soccer videos based on identifiable feature elements within a soccer video, Secondly we design Composite Petri-Net (CPN) models for semantic queries and use these to describe BSUCPNs for semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic event queries based on BSUCPNs to search interactively within soccer videos. Experimental results
based on recorded soccer broadcasts are used to illustrate the potential of this approach
Movement economy in soccer: Current data and limitations
Get PDFSoccer is an intermittent team-sport, where performance is determined by a myriad of psychological, technical, tactical, and physical factors. Among the physical factors, endurance appears to play a key role into counteracting the fatigue-related reduction in running performance observed during soccer matches. One physiological determinant of endurance is movement economy, which represents the aerobic energy cost to exercise at a given submaximal velocity. While the role of movement economy has been extensively examined in endurance athletes, it has received little attention in soccer players, but may be an important factor, given the prolonged demands of match play. For this reason, the current review discusses the nature, impact, and trainability of movement economy specific to soccer players. A summary of current knowledge and limitations of movement economy in soccer is provided, with an insight into future research directions, to make this important parameter more valuable when assessing and training soccer playersâ running performance
PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach
Full text linkThe problem of evaluating the performance of soccer players is attracting the
interest of many companies and the scientific community, thanks to the
availability of massive data capturing all the events generated during a match
(e.g., tackles, passes, shots, etc.). Unfortunately, there is no consolidated
and widely accepted metric for measuring performance quality in all of its
facets. In this paper, we design and implement PlayeRank, a data-driven
framework that offers a principled multi-dimensional and role-aware evaluation
of the performance of soccer players. We build our framework by deploying a
massive dataset of soccer-logs and consisting of millions of match events
pertaining to four seasons of 18 prominent soccer competitions. By comparing
PlayeRank to known algorithms for performance evaluation in soccer, and by
exploiting a dataset of players' evaluations made by professional soccer
scouts, we show that PlayeRank significantly outperforms the competitors. We
also explore the ratings produced by {\sf PlayeRank} and discover interesting
patterns about the nature of excellent performances and what distinguishes the
top players from the others. At the end, we explore some applications of
PlayeRank -- i.e. searching players and player versatility --- showing its
flexibility and efficiency, which makes it worth to be used in the design of a
scalable platform for soccer analytics
A semantic event detection approach for soccer video based on perception concepts and finite state machines
Get PDFA significant application area for automated video analysis technology is the generation of personalized highlights of sports events. Sports games are always composed of a range of significant events. Automatically detecting these events in a sports video can enable users to interactively select their own highlights. In this paper we propose a semantic event detection approach based on Perception Concepts and Finite State Machines to automatically detect significant events within soccer video. Firstly we define a Perception Concept set for soccer videos based on identifiable feature elements within a soccer video. Secondly we design PC-FSM models to describe semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic events and transfer event detection into graph matching. Experimental results based on recorded soccer broadcasts are used to illustrate the potential of this approach
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