Intelligent Agent Simulator in Massive Crowd

Mohamad, S., Nasir, F.M., Sunar, M.S., Isa, K., Hanifa, R.M., Shah, S.M., Ribuan, M.N., Ahmad, A. 1,4,6,7,8Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 1,2,3UTM-IRDA Digital Media Centre, Media and Game Innovation Centre of Excellence, Universiti Teknologi Malaysia, Johor, Malaysia 1,2,3Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia 5Centre for Diploma Studies, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 6Research Centre for Applied Electromagnetics, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

[1]  Mahanijah Md Kamal,et al.  Classification of leaf disease from image processing technique , 2018 .

[2]  F.E.H. Wijermans,et al.  Understanding crowd behaviour: simulating situated individuals , 2011 .

[3]  Yoosuf Nizam,et al.  An optimized low computational algorithm for human fall detection from depth images based on Support Vector Machine classification , 2017, 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).

[4]  Masaki Oshita,et al.  Simulating group formation and behaviour in dense crowd , 2016, VRCAI.

[5]  Matthias Rauterberg,et al.  Realistic Modeling of Agents in Crowd Simulations , 2014, 2014 5th International Conference on Intelligent Systems, Modelling and Simulation.

[6]  Dirk Helbing,et al.  Experimental study of the behavioural mechanisms underlying self-organization in human crowds , 2009, Proceedings of the Royal Society B: Biological Sciences.

[7]  A. J. Batista-Leyva,et al.  Symmetry Breaking in Escaping Ants , 2005, The American Naturalist.

[8]  Zhikun Wang.  Public Evacuation Process Modeling and Simulatiaon based on Cellular Automata , 2013 .

[9]  May Lim,et al.  Self-organized queuing and scale-free behavior in real escape panic , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Masaki Oshita,et al.  Making decision for the next step in dense crowd simulation using support vector machines , 2016, VRCAI.

[11]  Xiaoping Zheng,et al.  Modeling crowd evacuation of a building based on seven methodological approaches , 2009 .

[12]  Takefumi Matsunaga,et al.  Recognition of Walking Motion Using Support Vector Machine , 2007 .

[13]  Sah Hj Salam,et al.  Velocity Perception: Collision Handling Technique for Agent Avoidance Behavior , 2013 .

[14]  Masaki Oshita,et al.  Learning Motion Rules for Autonomous Characters from Control Logs Using Support Vector Machine , 2010 .

[15]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.