Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic improvements. In this paper, we present such a framework for evaluating object detection and tracking in video: specifically for face, text, and vehicle objects. This framework includes the source video data, ground-truth annotations (along with guidelines for annotation), performance metrics, evaluation protocols, and tools including scoring software and baseline algorithms. For each detection and tracking task and supported domain, we developed a 50-clip training set and a 50-clip test set. Each data clip is approximately 2.5 minutes long and has been completely spatially/temporally annotated at the I-frame level. Each task/domain, therefore, has an associated annotated corpus of approximately 450,000 frames. The scope of such annotation is unprecedented and was designed to begin to support the necessary quantities of data for robust machine learning approaches, as well as a statistically significant comparison of the performance of algorithms. The goal of this work was to systematically address the challenges of object detection and tracking through a common evaluation framework that permits a meaningful objective comparison of techniques, provides the research community with sufficient data for the exploration of automatic modeling techniques, encourages the incorporation of objective evaluation into the development process, and contributes useful lasting resources of a scale and magnitude that will prove to be extremely useful to the computer vision research community for years to come.

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Stationary spiral waves in liquid film flowing over a spinning disk have been observed in earlier experiments ͓H. Espig and R. Hoyle, "Waves in a thin liquid layer on a rotating disk," J. Fluid Mech. 22, 671 ͑1965͒; A. F. Charwat et al., "The flow and stability of thin liquid films on a rotating disk," ibid. 53, 227 ͑1972͒; G. Leneweit et al., "Surface instabilities of thin liquid film flow on a rotating disk," Exp. Fluids 26, 75 ͑1999͔͒.In the framework of a mathematical model derived by the integral method, it is shown that the waves develop due to nonaxisymmetric liquid feeding onto the spinning disk, and the wave shapes are approximated by the Archimedean spirals, whose coefficients depend on the Eckman number. The dependence has been confirmed by experimental data from recorded videos.

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General mathematical theory of evolutionary system developed earlier is implemented to various problems of artificial intelligence and intelligent agent mathematical modeling. Examples of application of this general theory to the evolutionary systems such as economics, education, and health care are also considered.