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In order to solve the moving objects shadow problem in foreground extraction of surveillance video images, a new cast shadow detection algorithm based on the YCbCr color space and topological cutting was proposed. Preliminary shadow removal was first performed based on the difference of the three components in the YCbCr color space of shadows and foregrounds. Besides, the maximum-flow/minimum-cut algorithm for image segmentation was optimized considering the topological constraints. The optimal segmentation of the foreground image was obtained during the continuous updating of the label. Finally, two sets of experiments were performed in video image sequences, including real surveillance videos and a well-known benchmark test set. By comparing with two other existing algorithms, the feasibility and effectiveness of the cast shadow detection algorithm were verified by the smooth border and higher recognition accuracy. In addition, the adaptability to foreground object density and different light intensities was measured in an airport terminal, showing that this algorithm can provide a high quality of moving foreground detection in surveillance video images and can be applied in monitoring of public places. [ABSTRACT FROM AUTHOR]

The aim of this paper was to analyse and model the behaviour decision-making of rescue crews in multi-helicopter collaborative search and rescue mission. Firstly, based on decision field theory, a dynamic behavioural decision-making model was put forward considering personal behaviour decision-making preference. Besides, considering physical characteristics, safety requirements and rescue crews' behaviour decision-making, a multi-helicopter collaborative search and rescue behaviour model was established. Then, based on the survey of four general aviation helicopter search and rescue companies, the search and rescue efficiency by teams composed of different decision-making preferences was simulated based on distributed ant colony algorithm in experiments. Results showed that rescue crews with different personal preferences have different behaviour characteristics. Besides, teams composed of mixed preferences are more efficient than teams composed of single preferences, and the most optimal composition way is when the positive type is slightly more than the conservative type and balanced type. [ABSTRACT FROM AUTHOR]