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Spatial game analytics and visualization

Anders Drachen, Matthias Schubert
2013 2013 IEEE Conference on Computational Inteligence in Games (CIG)  
However, the methods for analyzing and visualizing spatial and spatio-temporal patterns in player behavior being used by the game industry are not as diverse as the range of techniques utilized in game  ...  We summarize the current problems and challenges in the field, and present four key areas of spatial and spatio-temporal analytics: Spatial Outlier Detection, Spatial Clustering, Spatial Predictive Models  ...  Most available game heatmaps have been based on 3D-games using point data (X,Y); however, applications for generating 3D heatmaps (X,Y,Z) exist and allow for better interpretation of the effect of level  ... 
doi:10.1109/cig.2013.6633629 dblp:conf/cig/DrachenS13 fatcat:r2yiiux2ojgp3khn2li7trag54

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling

Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy
2020 Data mining and knowledge discovery  
Collective social media provides a vast amount of geo-tagged social posts, which contain various records on spatio-temporal behavior.  ...  In this paper, we address the following question: how to find representative subgroups of social posts, for which the spatio-temporal behavioral patterns are substantially different from the behavioral  ...  spatio-temporal modeling (BNPM)We consider the spatio-temporal behavior of geo-tagged social posts on the level of subgroups restricted by descriptive attributes.  ... 
doi:10.1007/s10618-020-00674-z fatcat:val2vqsm6bek5fyiwpd365e6my

Towards mega-modeling

Stefano Ceri, Themis Palpanas, Emanuele Della Valle, Dino Pedreschi, Johann-Christoph Freytag, Roberto Trasarti
2013 SIGMOD record  
Given spatio-temporal information, reconstruct trajectories and map them to edges among cells of a spatial tessellation, then partition the resulting network of cells so as to recognize regions with high  ...  A mega-module should expose commands to the enclosing environment that may alter its behavior, for instance by rising or by lowering confidence levels during analysis based on the quality of intermediate  ... 
doi:10.1145/2536669.2536673 fatcat:7pnwwccnhfbxrmv2hpbjevfmhe

Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective [article]

Wu Liu, Qian Bao, Yu Sun, Tao Mei
2021 arXiv   pre-print
Finally, we discuss the challenges and give deep thinking of promising directions for future research.  ...  We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation.  ...  Bottom-up • Graph partitioning-based model [118] , [119] ; • Temporal Flow Fields-based model [120] - [123] ; • Spatio-temporal associative embedding model KE-SIE [124] . related parts.  ... 
arXiv:2104.11536v1 fatcat:tdag2jq2vjdrjekwukm5nu7l6a

2021 Index IEEE Transactions on Multimedia Vol. 23

2021 IEEE transactions on multimedia  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Frame-Wise Detection of Double HEVC Compression by Learning Deep Spatio-Temporal Representations in Compression Domain.  ...  Wei, D., +, TMM 2021 2457-2470 Game theory Unsupervised Adversarial Instance-Level Image Retrieval.  ... 
doi:10.1109/tmm.2022.3141947 fatcat:lil2nf3vd5ehbfgtslulu7y3lq

Generative Models for Novelty Detection: Applications in abnormal event and situational change detection from data series [article]

Mahdyar Ravanbakhsh
2019 arXiv   pre-print
The results show the superior of our proposed methods in compare to the baselines and state-of-the-art methods.  ...  Novelty detection is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains observations that were not known at the training time.  ...  Acknowledgements First of all, I would like to thank my family (Farida, Hamid, Morteza); it is because of their never ending support that I have had the chance to progress in life.  ... 
arXiv:1904.04741v1 fatcat:fdwhsuaoi5hcdbjzcbjh2z6ydu

Deep Neural Mobile Networking [article]

Chaoyun Zhang
2020 arXiv   pre-print
In particular, deep learning based solutions can automatically extract features from raw data, without human expertise.  ...  performance requirements in terms of throughput, latency, and reliability.  ...  Wang et al. represent spatio-temporal dependencies in mobile traffic using graphs, and learn such dependencies using Graph Neural Networks [40] .  ... 
arXiv:2011.05267v1 fatcat:yz2zp5hplzfy7h5kptmho7mbhe

MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation

Jurgen Bernard, Nils Wilhelm, Bjorn Kruger, Thorsten May, Tobias Schreck, Jorn Kohlhammer
2013 IEEE Transactions on Visualization and Computer Graphics  
Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand.  ...  To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation  ...  ACKNOWLEDGMENTS The authors thank the 'Multimedia, Simulation and Virtual Reality Group' at the University of Bonn, Germany.  ... 
doi:10.1109/tvcg.2013.178 pmid:24051792 fatcat:emjtfkzp5fevrlnzxwso3z3ovu

PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach [article]

Luca Pappalardo and Paolo Cintia and Paolo Ferragina and Emanuele Massucco and Dino Pedreschi and Fosca Giannotti
2019 arXiv   pre-print
At the end, we explore some applications of PlayeRank -- i.e. searching players and player versatility --- showing its flexibility and efficiency, which makes it worth to be used in the design of a scalable  ...  The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events  ...  the spatio-temporal coordinates of the event over the soccer field.  ... 
arXiv:1802.04987v3 fatcat:qgq7b5rbnnfebnbubgf6ngcmwq

Smart instrumented training ranges: bringing automated system solutions to support critical domain needs

Amela Sadagic, Mathias Kölsch, Greg Welch, Chumki Basu, Chris Darken, Juan P. Wachs, Henry Fuchs, Herman Towles, Neil Rowe, Jan-Michael Frahm, Li Guan, Rakesh Kumar (+1 others)
2013 The Journal of Defence Modeling and Simulation: Applications, Methodology, Technology  
We describe BASE-IT (Behavioral Analysis and Synthesis for Intelligent Training), a system in development that aims to automate capture of training data and their analysis, performance evaluation, and  ...  It then analyzes movement and body postures, measures individual and squad-level performance, and compares it to standards and levels of performance expected in given situations.  ...  Funding This work was supported by the Office of Naval Research (ONR).  ... 
doi:10.1177/1548512912472942 fatcat:xbvsrbdp3zcyfmmed2g27agtsu

Visualizing public transit system operation with GTFS data: A case study of Calgary, Canada

Postsavee Prommaharaj, Santi Phithakkitnukoon, Merkebe Getachew Demissie, Lina Kattan, Carlo Ratti
2020 Heliyon  
The analysis module provides an insightful statistical summary and similarity measure and clustering results based on the transit operation characteristics.  ...  This paper aims to demonstrate the potential of GTFS data, specifically, the paper describes the development of a GTFS data visualization tool that displays spatial and temporal patterns of transit services  ...  Visual transformation of these O-D flows are performed and presented in the form of region-based heatmaps [6, 7, 9, 11] ; and line-based visualization [12, 13] . Zhou et al.  ... 
doi:10.1016/j.heliyon.2020.e03729 pmid:32322722 pmcid:PMC7160583 fatcat:2ifv5i25ajffnhhyajkjdlstj4

Artificial Intelligence for Social Good: A Survey [article]

Zheyuan Ryan Shi, Claire Wang, Fei Fang
2020 arXiv   pre-print
ways. (1) We quantitatively analyze the distribution and trend of the AI4SG literature in terms of application domains and AI techniques used. (2) We propose three conceptual methods to systematically  ...  Artificial intelligence for social good (AI4SG) is a research theme that aims to use and advance artificial intelligence to address societal issues and improve the well-being of the world.  ...  Ma et al. design a spatio-temporal pricing mechanism such that it is a subgame-perfect equilibrium for the driver to accept the dispatch [369] .  ... 
arXiv:2001.01818v1 fatcat:t6sn75k56nb3fbqi4vi52i2j44

Human mobility: Models and applications

Hugo Barbosa, Marc Barthelemy, Gourab Ghoshal, Charlotte R. James, Maxime Lenormand, Thomas Louail, Ronaldo Menezes, José J. Ramasco, Filippo Simini, Marcello Tomasini
2018 Physics reports  
This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems.  ...  Throughout the text the description of the theory is intertwined with real-world applications.  ...  law behavior for the waiting times) leads to mobility that appears sub-diffusive [85] at larger spatio-temporal scales.  ... 
doi:10.1016/j.physrep.2018.01.001 fatcat:4ewobqkarzho3dqjhd47iu3smu

Beyond the tracked line of sight: Gaze-driven user models [article]

David Geisler, Universitaet Tuebingen, Kasneci, Enkelejda (Prof. Dr.)
2021
The ensuing eye movements can be recorded and evaluated by state-of-the-art video-based eye-tracking systems.  ...  A small nerve tissue -- the retina -- on the back on an optical apparatus -- the eyeball -- provides a continuous flow of visual information of our environment.  ...  Figure 6.1.10 shows an example of simulated spatio-temporal signal flow.  ... 
doi:10.15496/publikation-53604 fatcat:2nxmddgt5nfmxc4bdjhefjrrke

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance

Daniel B. Neill, Karl A. Soetebier
2011 Emerging Health Threats Jour  
Acknowledgments Acknowledgments We would like to thank the Council of State and Territorial Epidemiologits for funding and the Center for Disease Control for selecting us to be part of this project.  ...  Acknowledgment This material is based upon work supported by the National Science Foundation under Grant No. IIS-0911032.  ...  The methodology incorporates Gaussian Markov random field (GMRF) and spatio-temporal conditional autoregressive (CAR) modeling.  ... 
doi:10.3402/ehtj.v4i0.11702 pmid:24149043 pmcid:PMC3261719 fatcat:3irrx5ne3bdntbyntliy33yzca
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