dc.contributor.author | Charalambous, Panayiotis | en |
dc.contributor.author | Karamouzas, I. | en |
dc.contributor.author | Guy, S. J. | en |
dc.contributor.author | Chrysanthou, Yiorgos L. | en |
dc.creator | Charalambous, Panayiotis | en |
dc.creator | Karamouzas, I. | en |
dc.creator | Guy, S. J. | en |
dc.creator | Chrysanthou, Yiorgos L. | en |
dc.date.accessioned | 2019-11-13T10:38:52Z | |
dc.date.available | 2019-11-13T10:38:52Z | |
dc.date.issued | 2014 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53683 | |
dc.description.abstract | We present a novel approach for analyzing the quality of multi-agent crowd simulation algorithms. Our approach is data-driven, taking as input a set of user-defined metrics and reference training data, either synthetic or from video footage of real crowds. Given a simulation, we formulate the crowd analysis problem as an anomaly detection problem and exploit state-of-the-art outlier detection algorithms to address it. To that end, we introduce a new framework for the visual analysis of crowd simulations. Our framework allows us to capture potentially erroneous behaviors on a per-agent basis either by automatically detecting outliers based on individual evaluation metrics or by accounting for multiple evaluation criteria in a principled fashion using Principle Component Analysis and the notion of Pareto Optimality. We discuss optimizations necessary to allow real-time performance on large datasets and demonstrate the applicability of our framework through the analysis of simulations created by several widely-used methods, including a simulation from a commercial game. © 2014 The Author(s) Computer Graphics Forum © 2014 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. | en |
dc.source | Computer Graphics Forum | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939424287&doi=10.1111%2fcgf.12472&partnerID=40&md5=e06f4b25b47c2d3a9997ade221f8cc1e | |
dc.subject | Statistics | en |
dc.subject | Multi agent systems | en |
dc.subject | Algorithms | en |
dc.subject | Pareto principle | en |
dc.subject | Principal component analysis | en |
dc.subject | Analysis of simulations | en |
dc.subject | Evaluation criteria | en |
dc.subject | Evaluation metrics | en |
dc.subject | Outlier detection algorithm | en |
dc.subject | Pareto-optimality | en |
dc.subject | Principle component analysis | en |
dc.subject | Real time performance | en |
dc.subject | User-defined metrics | en |
dc.title | A Data-Driven Framework for Visual Crowd Analysis | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1111/cgf.12472 | |
dc.description.volume | 33 | |
dc.description.issue | 7 | |
dc.description.startingpage | 41 | |
dc.description.endingpage | 50 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :8</p> | en |
dc.source.abbreviation | Comput.Graphics Forum | en |
dc.contributor.orcid | Chrysanthou, Yiorgos L. [0000-0001-5136-8890] | |
dc.contributor.orcid | Charalambous, Panayiotis [0000-0002-7230-5132] | |
dc.gnosis.orcid | 0000-0001-5136-8890 | |
dc.gnosis.orcid | 0000-0002-7230-5132 | |