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This paper presents a theoretical study into the use of optical systems for quantum computation. The study results pertain to quantum sampling and quantum communication and provide a basis for further research and the development of a physical implementation. We propose an optical superstructure that can implement specific computation processes and algorithms. The superstructure is composed of nonlinear optical units, such as beta barium borate crystals. The units are positioned in series, powered by a pulse laser pump, and culminate in a beam splitter that generates the output state of a number of entangled photon pairs. Computation is achieved by entanglement propagation via beam splitters and adjustable phase shifters, which set related parameters. Demonstrating a two-component case, we show how a series of cosine-based components can be implemented. The obtained results open a broad front for future research. Future work should investigate the construction of a quantum optimizer using quantum sampling methods and also investigate high-precision temporal voltage measurement, which is a key procedure for the construction of high-fidelity devices. [ABSTRACT FROM AUTHOR]

Tracking and action-recognition algorithms are currently widely used in video surveillance, monitoring urban activities and in many other areas. Their development highly relies on benchmarking scenarios, which enable reliable evaluations/improvements of their efficiencies. Presently, benchmarking methods for tracking and action-recognition algorithms rely on manual annotation of video databases, prone to human errors, limited in size and time-consuming. Here, using gained experiences, an alternative benchmarking solution is presented, which employs methods and tools obtained from the computer-game domain to create simulated video data with automatic annotations. Presented approach highly outperforms existing solutions in the size of the data and variety of annotations possible to create. With proposed system, a potential user can generate a sequence of random images involving different times of day, weather conditions, and scenes for use in tracking evaluation. In the design of the proposed tool, the concept of crowd simulation is used and developed. The system is validated by comparisons to existing methods. [ABSTRACT FROM AUTHOR]