- published: 14 May 2015
- views: 546
Preliminary crowd counting results at Grand Central Station, NY. Best viewed in 480p. Each group of people is outlined in red, and the estimate for the number of people in each group is printed in white. The overall estimate for the number of people in the scene is shown at the top. More information can be found in: "Scene Invariant Crowd Counting and Crowd Occupancy Analysis" David Ryan, Simon Denman, Sridha Sridharan and Clinton Fookes Video Analytics for Business Intelligence, Springer-Verlag, 2012 Paper: http://davidryan.net.au/files/David-Ryan_Scene-Invariant-Crowd-Counting_VABI-2012.pdf "Crowd Counting Using Group Tracking and Local Features" David Ryan, Simon Denman, Clinton Fookes and Sridha Sridharan Advanced Video and Signal-Based Surveillance (AVSS 2010) Paper: http://eprints...
Method for automatically locating and tracking groups of people in a video.
A computer vision, computer graphics and user experience design undergraduate project in software engineering at ÉTS (Montreal, Canada), by J-N, Blanchet and A. Millette. Editing is not perfectly synchronized, but the video is as close as possible to reality. If you look carefully, you'll notice some clips are inverted horizontally. This is because the configuration was not set properly at first, and the displayed content was mirrored. Music by Dan-O songs (http://www.danosongs.com/)
Results of a methio for tracking individual targets in high density unstructured crowded scenes, a class of crowded scenes where the motion of the crowd at any given location is multi-modal over time. To this end we adopted the Correlated Topic Model (CTM) in which each scene is associated with a set of behavior proportions,where behaviors represent distributions over low-level motion features. Unlike some existing formulations, our model is capable of capturing both the correlation amongst different patterns of behavior as well as allowing for the multi-modal nature of unstructured crowded scenes. In order to test our approach we performed experiments on a range of unstructured crowd domains, from cluttered time-lapse microscopy videos of cell populations in vitro to videos o...
Understanding Crowd Collectivity: A Meta-Tracking Approach, Authors: Afshin Dehghan Mahdi M. Kalayeh Center for Research in Computer Vision, University of Central Florida SUNw: Scene Understanding Workshop, CVPR 2015
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Studying the physics of pedestrian crowds from the rarefied to the dense regime in real life conditions. Automated recordings of pedestrians' heads and bodies from multiple depth sensors and particle tracking velocimetry algorithms. By A. Corbetta, C. Lee, J. Meeusen, A. Muntean and F. Toschi
"Realtime Multilevel Crowd Tracking using Reciprocal Velocity Obstacles" - IEEE International Conference on Pattern Recognition 2014 - Aniket Bera, Dinesh Manocha URL - http://gamma.cs.unc.edu/RCrowdT/ Abstract—We present a novel, realtime algorithm to compute
From the Kinolibrary archive film collections. To order the clip clean and high res visit http://www.kinolibrary.com. Clip ref A81 Crowds in France celebrate the end of WWI, great tracking shot through crowd of people cheering and celebrating
Seguimiento de personas, en azul el groundtruth y en rojo el seguimiento del algoritmo de filtro de partículas hibridado con algoritmo memético.
Tracking crowd of pedestrian with occlusion using prior info 94% correct.
August 2005 Professor Roberto Cipolla and Gabriel Brostow at the Department of Engineering are working on a project to detect and track individuals in crowd situations. Roberto and Gabriel met with London Transport and West Anglia Great Northern Railway (Wagn), who have different reasons to need to detect and track people in crowds. London Underground use cameras at each of their stations to watch their passengers. The cameras are filtered to some extent; if no one is moving, those cameras are not shown on the monitoring screens. Hundreds of cameras are monitored by staff watching the images, as they switch from one camera to the next. It is impossible to have the manpower to observe all these cameras closely enough to watch for all suicide attempts. Approximately two thirds of suicide at...
A pretty young woman of Indian ethnicity looks thoughtful as she walks through a busy crowd. No one but her are recognizable. This is a royalty free stock footage clip. If you'd like to use it in your production, please purchase it at pond5.com the link below. http://www.pond5.com/stock-footage/43563362/young-woman-walks-through-crowd-front-tracking-shot.html This clip is also available on shutterstock.com and clipcanvas.com. For deep discounts on bundled stock footage: http://creativestock.storypaths.net/