Adel Hafeezallah1, Ahlam Al-Dhamari2,3,*, Syed Abd Rahman Abu-Bakar2
Computer Systems Science and Engineering, Vol.47, No.1, pp. 593-611, 2023, DOI:10.32604/csse.2023.039479
Abstract Visual motion segmentation (VMS) is an important and key part of many intelligent crowd systems. It can be used to figure out the flow behavior through a crowd and to spot unusual life-threatening incidents like crowd stampedes and crashes, which pose a serious risk to public safety and have resulted in numerous fatalities over the past few decades. Trajectory clustering has become one of the most popular methods in VMS. However, complex data, such as a large number of samples and parameters, makes it difficult for trajectory clustering to work well with accurate motion segmentation results. This study introduces a… More >
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