The algorithm for people counting in crowded scenes, based on the idea of virtual gate which uses optical flow method is presented. The concept and practical application of the developed algorithm under real conditions is depicted. The aim of the work is to estimate the number of people passing through entrances of a large sport hall. The most challenging problem was the unpredicted behavior of people while entering the building. The examined flow of people fluctuated between individual persons and dense crowd. A series of experiments during sport and entertainment events was made. The results of the experiments show a high efficiency of the elaborated algorithm.
Abstract.In this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual brain rhythms. In particular, the recognition of alpha and beta states is examined to assess whether synchronization occurred. Two independent methods of hemispheric synchronization analysis are given, i.e. the first consisted in calculating statistical parameters for the entire signal registered and the second one in using wavelet-based feature statistics for different lengths of time windows, and then discussed. Perspectives of the system development are shown in the conclusions.
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