In this paper, we describe a statistical method to detect highlights in a baseball game video. The input video is first segmented into scene shots, within which the camera motion is continuous. Our approach is based on the observations that 1) most highlights in baseball games are composed of certain types of scene shots and 2) those scene shots exhibit special transition context in time. To ex...

to evaluate and predict component-based software security, a two-dimensional model of software security is proposed by stochastic petri net in this paper. in this approach, the software security is modeled by graphical presentation ability of petri nets, and the quantitative prediction is provided by the evaluation capability of stochastic petri net and the computing power of markov chain. each...

The air transport industry is seeking to manage risks in air travels. Its main objective is to detect abnormal behaviors in various flight conditions. The current methods have some limitations and are based on studying the risks and measuring the effective parameters. These parameters do not remove the dependency of a flight process on the time and human decisions. In this paper, we used an HMM...

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We present the design and development of a Hidden Markov Model for the division of news broadcasts into story segments. Model topology, and the textual features used, are discussed, together with the non-parametric estimation techniques that were employed for obtaining estimates for both transition and observation probabilities. Visualization methods developed for the analysis of system perform...

To determine the possibility of predicting viewer’s internal states using the hidden Markov model, several features of eye movements were introduced to the model. Performance was measured using the data from a set of eye movement features recorded during recall tests which consisted of observations of three levels of task difficulty. The features were the temporal appearances of fixations and s...

This paper describes the use of phonological knowledge to enhance current audio word spotting technology based on Hidden Markov Model. It reports on the result of an word-spotting experiment done on an audio data recorded from a live conference. The result of the experiment demonstrates the positive contribution of phonological knowledge towards audio word-spotting.