Precision Of Events Research Articles

Automatic Detection Algorithm of Football Events in Videos.

The purpose is to effectively solve the problems of high time cost, low detection accuracy, and difficult standard training samples in video processing. Based on previous investigations, football game videos are taken as research objects, and their shots are segmented to extract the keyframes. The football game videos are divided into different semantic shots using the semantic annotation method. The key events and data in the football videos are analyzed and processed using a combination of artificial rules and a genetic algorithm. Finally, the performance of the proposed model is evaluated and analyzed by using concrete example videos as data sets. Results demonstrate that adding simple artificial rules based on the classic semantic annotation algorithms can save a lot of time and costs while ensuring accuracy. The target events can be extracted and located initially using a unique lens. The model constructed by the genetic algorithm can provide higher accuracy when the training samples are insufficient. The recall and precision of events using the text detection method can reach 96.62% and 98.81%, respectively. Therefore, the proposed model has high video recognition accuracy, which can provide certain research ideas and practical experience for extracting and processing affective information in subsequent videos.

Patterns of Preference for Numerical and Verbal Probabilities

We report results of an experiment designed to test a principle formulated by Budescu and Wallsten (1995), that, when communicating uncertainty information, mode choices are sensitive to sources and degrees of vagueness. In addition, we examined subjects’ efficacy in using such uncertainty information as a function of communication mode, source, and vagueness. In phase one of the experiment, subjects in a dyad used precise (numerical) or imprecise (verbal) expressions to communicate to a remote partner precise or vague uncertainty about the likelihoods of events. Spinner outcomes were used to generate precise uncertainty while answers to almanac questions were used to elicit vague uncertainty. In phase two, subjects saw the events paired with their partners’ estimates of similar events, and were asked to gamble on one event from each pair. Communication mode preferences were measured as the relative frequency that subjects chose the numerical mode to either express or receive uncertainty information regarding the events. Efficacy was measured as the relative frequency that subjects choose from the pair the event associated with the objectively more probable uncertainty expression. Underlying uncertainty interacted with direction of communication to affect preferences for modes of expression of the probabilities. Subjects preferred precise (numerical) information, especially for precise events (spinners). For vague events (questions), their preference for precise (numerical) information was stronger when receiving than when communicating information. Similar preferences were reflected in the efficiency of subsequent gamble decisions based on the probability estimates. Specifically, decisions were more efficacious (i.e. consistent with Expected Utility) when degrees of precision in events and estimates matched. © 1997 by John Wiley & Sons, Ltd.