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007 cr nn 008mamaa
008 131122s2013 xxu| s |||| 0|eng d
020 _a9781461484837
_9978-1-4614-8483-7
024 7 _a10.1007/978-1-4614-8483-7
_2doi
050 4 _aT385
050 4 _aTA1637-1638
050 4 _aTK7882.P3
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.6
_223
245 1 0 _aModeling, Simulation and Visual Analysis of Crowds
_h[electronic resource] :
_bA Multidisciplinary Perspective /
_cedited by Saad Ali, Ko Nishino, Dinesh Manocha, Mubarak Shah.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXI, 411 p. 208 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aThe International Series in Video Computing,
_x1571-5205 ;
_v11
505 0 _aModeling, Simulation and Visual Analysis of Crowds: A Multidisciplinary Perspective -- On Force-based Modeling of Pedestrian Dynamics -- Connection between Microscopic and Macroscopic Models -- Analysis of Crowd Dynamics with Laboratory Experiments -- Modeling a Crowd of Groups: Multidisciplinary and Methodological Challenges -- Scalable Solutions for Simulating, Animating, and Rendering Real-Time Crowds of Diverse Virtual Humans -- Authoring Multi-Actor Behaviors in Crowds with Diverse Personalities -- Virtual Tawaf: A Velocity-space-based Solution for Simulating Heterogeneous Behavior in Dense Crowds -- Crowd Flow Segmentation using Lagrangian Particle Dynamics -- Modeling Crowd Flow for Video Analysis of Crowded Scenes -- Pedestrian Interaction in Tracking: The Social Force Model and Global Optimization Methods -- Surveillance of Crowded Environments: Modeling the Crowd by its Global Properties -- Inferring Leadership from Group Dynamics Using Markov Chain Monte Carlo Methods -- Crowd Counting and Profiling: Methodology and Evaluation -- Anomaly Detection in Crowded Scenes: A Novel Framework based on Swarm Optimization and Social Force Modeling.
520 _aOver the last several years there has been a growing interest in developing computational methodologies for modeling and analyzing movements and behaviors of 'crowds' of people. This interest spans several scientific areas that includes Computer Vision, Computer Graphics, and Pedestrian Evacuation Dynamics. Despite the fact that these different scientific fields are trying to model the same physical entity (i.e. a crowd of people), research ideas have evolved independently. As a result each discipline has developed techniques and perspectives that are characteristically their own. The goal of this book is to provide the readers a comprehensive map towards the common goal of better analyzing and synthesizing the pedestrian movement in dense, heterogeneous crowds. The book is organized into different parts that consolidate various aspects of research towards this common goal, namely the modeling, simulation, and visual analysis of crowds. Through this book, readers will see the common ideas and vision as well as the different challenges and techniques, that will stimulate novel approaches to fully grasping "crowds.".
650 0 _aComputer science.
650 0 _aComputer simulation.
650 0 _aComputer graphics.
650 0 _aBehavioral sciences.
650 1 4 _aComputer Science.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
650 2 4 _aSimulation and Modeling.
650 2 4 _aBehavioral Sciences.
700 1 _aAli, Saad.
_eeditor.
700 1 _aNishino, Ko.
_eeditor.
700 1 _aManocha, Dinesh.
_eeditor.
700 1 _aShah, Mubarak.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461484820
830 0 _aThe International Series in Video Computing,
_x1571-5205 ;
_v11
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-8483-7
912 _aZDB-2-SCS
942 _cEBK
999 _c57636
_d57636