Title :
Online pedestrian group walking event detection using spectral analysis of motion similarity graph
Author :
Vahid Bastani;Damian Campo;Lucio Marcenaro;Carlo Regazzoni
Author_Institution :
University of Genoa, DITEN, Via all´Opera Pia, 11A - 16145 Genova (GE), Italy
Abstract :
A method for online identification of group of moving objects in the video is proposed in this paper. This method at each frame identifies group of tracked objects with similar local instantaneous motion pattern using spectral clustering on motion similarity graph. Then, the output of the algorithm is used to detect the event of more than two object moving together as required by PETS2015 challenge. The performance of the algorithm is evaluated on the PETS2015 dataset.
Keywords :
"Clustering algorithms","Legged locomotion","Kalman filters","Cameras","Trajectory","Eigenvalues and eigenfunctions","Hidden Markov models"
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on
DOI :
10.1109/AVSS.2015.7301744
