Meta-tracking and Dominant Motion Patterns at the Macroscopic Crowd Level (CROSBI ID 701538)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Matković, Franjo ; Ribarić, Slobodan
engleski
Meta-tracking and Dominant Motion Patterns at the Macroscopic Crowd Level
This paper presents a method for crowd motion segmentation and generating dominant motion patterns at the macroscopic crowd level, where a crowd is treated as an entity. In this approach, the dominant motion patterns, as a base for behaviour analysis of a mass of people, are the focus of interest. Dominant motion patterns are generated based on meta-trajectories. A meta-trajectory is defined as a set of tracklets and/or trajectories of entities in the crowd. The entities are particles initially organized as a uniform grid which is overlaid on a flow field. To estimate the flow field, a dense optical flow is used. Based on advection of the particles, tracklets/trajectories are obtained. They are grouped by a graph-based clustering algorithm and meta-trajectories are obtained. By overlapping meta-trajectories with the quantized orientation of the average optical flow field dominant motion patterns are obtained. The preliminary experimental results of the proposed method are given for a subset of UCF dataset, a subset of Crowd Saliency Detection dataset, our own FER dataset and computer crowd simulation videos of characteristic behaviour.
Macroscopic crowd level Crowd analysis Optical flow Particle advection Meta-trajectory Dominant motion pattern
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Podaci o prilogu
382-393.
2021.
objavljeno
10.1007/978-981-16-1103-2_32
Podaci o matičnoj publikaciji
Singh S.K., Roy P., Raman B., Nagabhushan P. (eds) Computer Vision and Image Processing. CVIP 2020. Communications in Computer and Information Science, vol 1378. Springer, Singapore
Singh S.K. ; Roy P. ; Raman B. ; Nagabhushan P.
Singapur: Springer
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predavanje
29.02.1904-29.02.2096