Дисертації з теми "Pedestrian crowds"
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Johansson, Anders. "Data-Driven Modeling of Pedestrian Crowds." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2009. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-20900.
Повний текст джерелаAls diese Dissertation im Januar 2005 begonnen wurde, nutzten wissenschaftliche Untersuchungen von Fußgängern fast ausschließlich Computersimulationen und Evakuierungsexperimente. Seit dem haben viele Wissenschaftler an einer Verbesserung der Methoden gearbeitet. Heute werden empirische Daten mit Hilfe von Videoanalysen, Laser- und Infrarotkameras erhoben.Jedoch konzentrieren sich viele dieser Arbeiten auf künstliche Setups, in denen sich Fußgängermassen durch Korridore und Engpässe bewegen. Diese Experimente erlauben es, Massenbewegungen zu verstehen. Jedoch gibt es immer noch Forschungslücken. Es ist schwierig, unter solch kontrollierten Bedingungen Fortschritte darin zu erzielen, die auftretenden Dyamiken bei großen Katastrophen zu verstehen, in denen manchmal Hunderttausende oder sogar Millionen von Fußgängern involviert sind. Immer wieder kommt es zu Katastrophen in großen Menschenmengen. Leider sind von diesen Ereignissen häufig nur qualitative Informationen anstelle von quantitativen Daten erhältlich. Es ergab sich die besondere Gelegenheit, quantitatives Filmmaterial über eine Katastrophe in Mina (Königreich Saudi--Arabien) zu erhalten. Dort starben am 12. Januar 2006 hunderte von Pilgern während der jährlichen muslimischen Pilgerfahrt nach Mekka. Mit dem erhobenen Videomaterial konnte nachvollzogen werden, wie die Menschenmenge zuerst unbehindert fließen konnte, dann immer dichter wurde und wie es schließlich zur Katastrophe kam. Von den Erkenntnissen der Analyse der oben beschriebenen Katastrophe konnten neue Methoden entwickelt werden, die dabei helfen können, ähnliche Katastrophen in Zukunft zu vermeiden. Ein weiterer Beitrag dieser Dissertation besteht darin, einige Annahmen, die üblicherweise bei der Simulation von Fußgängerdynamiken gemacht werden, in Frage zu stellen und zu überarbeiten. Diese Annahmen sind: (1) Ein Fußgänger verhindert Zusammenstöße, indem er seine Schrittgeschwindigkeit so verändert, dass seine Beschleunigung exponentiell mit der Distanz zu dem zu umgehenden Fußgänger oder Objekt abnimmt. (2) Ein Fußgänger zeigt stärkere Reaktionen auf Ereignisse, die vor ihm passieren, als auf Ereignisse, die hinter ihm passieren. (3) Die Bewegung eines in einer Menschenmenge befindlichen Fußgängers folgt immer dem Strömungs--Dichte Verhältnis, was als Fundamental-Diagramm bezeichnet wird. (4) Die Laufgeschwindigkeit eines Fußgängers erreicht bei maximaler Menschendichte einem Wert von 0 m/s. Die ersten beiden Annahmen wurden von den empirischen Daten bestätigt. Unsere Analysen zeigen jedoch, dass die Annahmen 3 und 4 nicht immer gültig sind. Somit müssen Standardtheorien von Fußgängerdynamiken überarbeitet werden. Im Anschluß an die Analyse dieser fundamentalen Aspekte von Fußgängerverhalten und dem Verhalten bei Ausweichmanövern wird das Social-Force-Modell weiterentwickelt. Um auf vorhergehenden Arbeiten aufzubauen und um die oben beschriebene Katastrophe analysieren zu können, werden Algorithmen für die Video-Verfolgung von Fußgängerbewegungen entwickelt. Das Neue bei diesem Teil der Arbeit liegt nicht nur in dem verwendeten Verfahren selbst, sondern auch in der Einzigartigkeit und der großen Menge an verwendeten Daten, die mit diesem Verfahren analysiert werden. Ein zentrales Ziel dieser Arbeit besteht demnach in einer wissenschaftlichen Weiterentwicklung von theoretischen Modellen und kontrollierten Laborexperimenten hin zu Modellen, die unter realen Bedingungen tatsächlich anwendbar sind. Die Analyse von Fußgängern ist ein interdisziplinäres Feld, das von verschiedenen wissenschaftlichen Disziplinen mit verschiedenen Zielen betrieben wird. Leider gab es bislang wenig Bemühungen, die Resultate innerhalb dieser Teilgebiete im Rahmen einer konsistenten Theorie zu vereinen. Als seltene Ausnahmen können die Arbeiten von Teknomo und Antonini genannt werden. Diese Dissertation verfolgt das Ziel, diese theoretische Vereinigung weiter voran zu treiben. Dazu muss man zwischen der Neuerfindung des Rades und der Wiederverwendung nicht geprüfter Resultate abwägen. Dementsprechend ist ein Teil dieser Dissertation dem Vorhaben gewidmet, bisherige Forschung im Lichte empirischer Daten und neuer Methoden zu evaluieren. Da sich die Arbeit mit recht unterschiedlichen Aspekten von Fußgängerverhalten beschäftigt, konzentriert sich die Analyse in verschiedenen Teilen der Arbeit auf einige ausgewählte, alternative Modelle. Insbesondere bei der Modellierung und Simulation wird anstelle einer eingehenden Übersicht verschiedener Modelle eine Diskussion des speziellen Social-Force Modells präsentiert
Vandoni, Jennifer. "Ensemble Methods for Pedestrian Detection in Dense Crowds." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS116/document.
Повний текст джерелаThis study deals with pedestrian detection in high- density crowds from a mono-camera system. The detections can be then used both to obtain robust density estimation, and to initialize a tracking algorithm. One of the most difficult challenges is that usual pedestrian detection methodologies do not scale well to high-density crowds, for reasons such as absence of background, high visual homogeneity, small size of the objects, and heavy occlusions. We cast the detection problem as a Multiple Classifier System (MCS), composed by two different ensembles of classifiers, the first one based on SVM (SVM-ensemble) and the second one based on CNN (CNN-ensemble), combined relying on the Belief Function Theory (BFT) to exploit their strengths for pixel-wise classification. SVM-ensemble is composed by several SVM detectors based on different gradient, texture and orientation descriptors, able to tackle the problem from different perspectives. BFT allows us to take into account the imprecision in addition to the uncertainty value provided by each classifier, which we consider coming from possible errors in the calibration procedure and from pixel neighbor's heterogeneity in the image space. However, scarcity of labeled data for specific dense crowd contexts reflects in the impossibility to obtain robust training and validation sets. By exploiting belief functions directly derived from the classifiers' combination, we propose an evidential Query-by-Committee (QBC) active learning algorithm to automatically select the most informative training samples. On the other side, we explore deep learning techniques by casting the problem as a segmentation task with soft labels, with a fully convolutional network designed to recover small objects thanks to a tailored use of dilated convolutions. In order to obtain a pixel-wise measure of reliability about the network's predictions, we create a CNN- ensemble by means of dropout at inference time, and we combine the different obtained realizations in the context of BFT. Finally, we show that the output map given by the MCS can be employed to perform people counting. We propose an evaluation method that can be applied at every scale, providing also uncertainty bounds on the estimated density
Berton, Florian. "Immersive virtual crowds : evaluation of pedestrian behaviours in virtual reality." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S056.
Повний текст джерелаVirtual Reality (VR) has become more and more used as a tool to study human behaviour. Indeed, its use provides absolute control over experimental conditions and can reproduce the same stimulus for all participants. In this thesis, we use VR to investigate pedestrian behaviour in crowds in order to subsequently improve crowd simulators. In particular we are interested in a coupled analysis of locomotion and gaze in order to understand and model the interaction neighbourhood during navigation. In our first work, we evaluated the impact of VR on gaze activity during an interaction between two pedestrians, in a study where participants performed a collision avoidance task in a real and virtual environment. We then studied a more complex situation which is the navigation in a crowded street. We again evaluated the impact of VR on gaze activity and then explored the impact of crowd density on this activity. Finally, in a third study we simulated the collisions that occur when navigating in a dense crowd using haptic rendering, and evaluated the influence of such rendering on participants' locomotion. In conclusion, our results show that VR is a relevant tool to study pedestrian behaviour in crowds. In particular, with recent technological innovations, this tool is appropriate for the study of gaze activity, which to date has been little explored for this kind of situation
Feng, Weinan. "Multiple Human Body Detection in Crowds." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-12352.
Повний текст джерелаMakmul, Juntima [Verfasser], and Simone [Akademischer Betreuer] Göttlich. "Microscopic and macroscopic models for pedestrian crowds / Juntima Makmul. Betreuer: Simone Göttlich." Mannheim : Universitätsbibliothek Mannheim, 2016. http://d-nb.info/1099910633/34.
Повний текст джерелаBain, Nicolas. "Hydrodynamics of polarized crowds : experiments and theory." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN078/document.
Повний текст джерелаModelling crowd motion is central to situations as diverse as risk prevention in mass events and visual effects rendering in the motion picture industry. The difficulty to perform quantitative measurements in model experiments, and the lack of reference experimental system, have however strongly limited our ability to model and control pedestrian flows. The aim of this thesis is to strengthen our understanding of human crowds, following two distinct approaches.First, we designed a numerical model to study the lane formation process among bidirectional flows of motile particles. We first evidenced the existence of two distinct phases: one fully laned and one homogeneously mixed, separated by a critical phase transition, unique to active systems. We then showed with a hydrodynamic approach that the mixed phase is algebraically correlated in the direction of the flow. We elucidated the origin of these strong correlations and proved that they were a universal feature of any system of oppositely moving particles, active of passive.Second, we conducted a substantial experimental campaign to establish a model experiment of human crowds. For that purpose we performed systematic measurements on crowds composed of tens of thousands of road-race participants in start corrals, a geometrically simple setup. We established that speed information propagates through polarized crowds over system spanning scales, while orientational information is lost in a few seconds. Building on these observations, we laid out a hydrodynamic theory of polarized crowds and demonstrated its predictive power
KHAN, SULTAN DAUD. "Automatic Detection and Computer Vision Analysis of Flow Dynamics and Social Groups in Pedestrian Crowds." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/102644.
Повний текст джерелаBisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Повний текст джерелаBisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Повний текст джерелаZäll, Emma. "Modelling Pedestrian-Induced Vertical Vibrations of Footbridges." Thesis, Umeå universitet, Institutionen för fysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-101831.
Повний текст джерелаNär en folksamling går över en gångbro uppstår vibrationer i gångbron. Dessa vibrationer påverkar brons användbarhet och kan ge upphov till obehagskänsla hos fotgängarna, vilket gör att vibrationerna i största möjliga utsträckning bör motverkas. I nuläget saknas pålitliga modeller för att beskriva den dynamiska last en gångbro utsätts för när en folksamling går över den. Således föreligger ett behov att utveckla en sådan modell. Under de senaste decennierna har mycket forskning utförts inom området människoinducerade vibrationer i gångbroar. Dock har merparten av denna forskning berört endast laterala vibrationer. Detta projekt däremot, har genomförts med syftet att, med ett noggrant resultat, modellera människoinducerade vertikala vibrationer i en generell gångbro. För att uppnå detta har jag utgått från en befintlig modell och från den utvecklat en ny modell bestående av tre delmodeller. De tre delmodellerna är: en modell som beskriver hur folksamlingen rör sig över gångbron, en modell som beskriver den kraft det mänskliga fotsteget uträttar på gångbron och en modell som beskriver interaktionen mellan fotgängarna och gångbron. För att uppnå statistiskt tillförlitliga resultat har modellen som utvecklats i detta projekt använts för att utföra åtskilliga simuleringar av människoinducerade vertikala vibrationer i en specifik gångbro. Om vi medelvärdesbildar resultaten över simuleringarna framgår det att modellen som utvecklats ger ett resultat som avviker med 7 % från experimentellt data. Detta gäller för den maximala accelerationen vid gångbrons mittpunkt. Den resulterande dynamiska responsen ser kvalitativt sett bra ut, medan den kvantitativa avvikelsen är större än vi hoppats på. Därför drar vi slutsatsen att vidare förbättringar av modellen behövs för att den ska kunna användas till att på ett noggrant sätt modellera människoinducerade vertikala vibrationer i gångbroar.
Haciomeroglu, Murat. "Populating virtual urban environments with crowds of pedestrians in real-time." Thesis, University of East Anglia, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518360.
Повний текст джерелаQiu, Fasheng. "A Framework for Group Modeling in Agent-Based Pedestrian Crowd Simulations." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/cs_diss/56.
Повний текст джерелаNishinari, Katsuhiro, Satoshi Kokubo, and Kazuhiro Yamamoto. "Simulation for pedestrian dynamics by real-coded cellular automata (RCA)." Elsevier, 2007. http://hdl.handle.net/2237/20045.
Повний текст джерелаShbib, Reda. "Pedestrians counting and event detection in crowded environment." Thesis, University of Portsmouth, 2015. https://researchportal.port.ac.uk/portal/en/theses/pedestrians-counting-and-event-detection-in-crowded-environment(76554ebe-0c0f-4409-9905-79b2f0b62bac).html.
Повний текст джерелаPop, Dănuţ Ovidiu. "Multi-task cross-modality deep learning for pedestrian risk estimation Multi-task deep learning for pedestrian detection, action recognition and time to cross prediction." Thesis, Normandie, 2019. http://www.theses.fr/2019NORMIR06.
Повний текст джерелаThis PhD thesis is the result of my research work in the machine learning, image processing and intelligent transportation field for solving the problem of multi-task pedestrian protection system (PPS) including not only pedestrian classification, detection and tracking, but also pedestrian action-unit classification and prediction, and finally pedestrian risk estimation. Moreover, our PPS system uses original cross-modality deep learning approaches. The goal of our research work is to develop an intelligent pedestrian protection component-based only on single stereo vision system using an optimal cross-modality deep learning architecture in order to classify the current pedestrian action, predict their next actions and finally to estimate the pedestrian risk by the time to cross for each pedestrian. First, we investigate the classification component where we analyzed how learning representations from one modality would enable recognition for other modalities within various deep learning, which one term as cross-modality learning. Second, we study how the cross-modality learning improves an end-to-end the pedestrian action
Chen, Ming. "Characterization of Pedestrian Electromagnetic Scattering at 76-77GHz." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385579499.
Повний текст джерелаMANENTI, LORENZA ALESSANDRA. "Agent-based proxemic dynamics: crowd and groups simulation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/42374.
Повний текст джерелаSorrentino, Luigi. "Simulation and optimization of crowd dynamics using a multiscale model." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/318.
Повний текст джерелаIn the last decades, the modeling of crowd motion and pedestrian .ow has attracted the attention of applied mathematicians, because of an increasing num- ber of applications, in engineering and social sciences, dealing with this or similar complex systems, for design and optimization purposes. The crowd has caused many disasters, in the stadiums during some major sporting events as the "Hillsborough disaster" occurred on 15 April 1989 at Hills- borough, a football stadium, in She¢ eld, England, resulting in the deaths of 96 people, and 766 being injured that remains the deadliest stadium-related disaster in British history and one of the worst ever international football accidents. Other example is the "Heysel Stadium disaster" occurred on 29 May 1985 when escaping, fans were pressed against a wall in the Heysel Stadium in Brussels, Belgium, as a result of rioting before the start of the 1985 European Cup Final between Liv- erpool of England and Juventus of Italy. Thirty-nine Juventus fans died and 600 were injured. It is well know the case of the London Millennium Footbridge, that was closed the very day of its opening due to macroscopic lateral oscillations of the structure developing while pedestrians crossed the bridge. This phenomenon renewed the interest toward the investigation of these issues by means of mathe- matical modeling techniques. Other examples are emergency situations in crowded areas as airports or railway stations. In some cases, as the pedestrian disaster in Jamarat Bridge located in South Arabia, mathematical modeling and numerical simulation have already been successfully employed to study the dynamics of the .ow of pilgrims, so as to highlight critical circumstances under which crowd ac- cidents tend to occur and suggest counter-measures to improve the safety of the event. In the existing literature on mathematical modeling of human crowds we can distinguish two approaches: microscopic and macroscopic models. In model at microscopic scale pedestrians are described individually in their motion by ordinary di¤erential equations and problems are usually set in two-dimensional domains delimiting the walking area under consideration, with the presence of obstacles within the domain and a target. The basic modeling framework relies on classical Newtonian laws of point. The model at the macroscopic scale consists in using partial di¤erential equations, that is in describing the evolution in time and space of pedestrians supplemented by either suitable closure relations linking the velocity of the latter to their density or analogous balance law for the momentum. Again, typical guidelines in devising this kind of models are the concepts of preferred direction of motion and discomfort at high densities. In the framework of scalar conservation laws, a macroscopic onedimensional model has been proposed by Colombo and Rosini, resorting to some common ideas to vehicular tra¢ c modeling, with the speci.c aim of describing the transition from normal to panic conditions. Piccoli and Tosin propose to adopt a di¤erent macroscopic point of view, based on a measure-theoretical framework which has recently been introduced by Canuto et al. for coordination problems (rendez-vous) of multiagent systems. This approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, provide an estimate of the space occupancy by pedestrians at successive time steps. From the modeling point of view, this setting is particularly suitable to treat nonlocal interactions among pedestrians, obstacles, and wall boundary conditions. A microscopic approach is advantageous when one wants to model di¤erences among the individuals, random disturbances, or small environments. Moreover, it is the only reliable approach when one wants to track exactly the position of a few walkers. On the other hand, it may not be convenient to use a microscopic approach to model pedestrian .ow in large environments, due to the high com- putational e¤ort required. A macroscopic approach may be preferable to address optimization problems and analytical issues, as well as to handle experimental data. Nonetheless, despite the fact that self-organization phenomena are often visible only in large crowds, they are a consequence of strategical behaviors devel- oped by individual pedestrians. The two scales may reproduce the same features of the group behavior, thus providing a perfect matching between the results of the simulations for the micro- scopic and the macroscopic model in some test cases. This motivated the multiscale approach proposed by Cristiani, Piccoli and Tosin. Such an approach allows one to keep a macroscopic view without losing the right amount of .granularity,.which is crucial for the emergence of some self-organized patterns. Furthermore, the method allows one to introduce in a macroscopic (averaged) context some micro- scopic e¤ects, such as random disturbances or di¤erences among the individuals, in a fully justi.able manner from both the physical and the mathematical perspec- tive. In the model, microscopic and macroscopic scales coexist and continuously share information on the overall dynamics. More precisely, the microscopic part tracks the trajectories of single pedestrians and the macroscopic part the density of pedestrians using the same evolution equation duly interpreted in the sense of measures. In this respect, the two scales are indivisible. Starting from model of Cristiani, Piccoli and Tosin we have implemented algo- rithms to simulate the pedestrians motion toward a target to reach in a bounded area, with one or more obstacles inside. In this work di¤erent scenarios have been analyzed in order to .nd the obstacle con.guration which minimizes the pedes- trian average exit time. The optimization is achieved using to algorithms. The .rst one is based on the exhaustive exploration of all positions: the average exit time for all scenarios is computed and then the best one is chosen. The second algorithm is of steepest descent type according to which the obstacle con.guration corresponding to the minimum exit time is found using an iterative method. A variant has been introduced to the algorithm so to obtain a more e¢ cient proce- dure. The latter allows to .nd better solutions in few steps than other algorithms. Finally we performed other simulations with bounded domains like a classical .at with .ve rooms and two exits, comparing the results of three di¤erent scenario changing the positions of exit doors. [edited by author]
X n.s.
GORRINI, ANDREA. "Empirical studies and computational results of a proxemic - based model of pedestrian crowd dynamics." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/50254.
Повний текст джерелаXi, Hui. "A DDDAS-Based Multi-Scale Framework for Pedestrian Behavior Modeling and Interactions with Drivers." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/306361.
Повний текст джерелаCORBETTA, ALESSANDRO. "Multiscale Crowd Dynamics: Physical Analysis, Modeling and Applications." Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2659720.
Повний текст джерелаCastle, Christian James Edward. "Agent-Based modelling of pedestrian evacuation: study of London's King's Cross underground station." Thesis, University College London (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.498192.
Повний текст джерелаPellicanò, Nicola. "Tackling pedestrian detection in large scenes with multiple views and representations." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS608/document.
Повний текст джерелаPedestrian detection and tracking have become important fields in Computer Vision research, due to their implications for many applications, e.g. surveillance, autonomous cars, robotics. Pedestrian detection in high density crowds is a natural extension of such research body. The ability to track each pedestrian independently in a dense crowd has multiple applications: study of human social behavior under high densities; detection of anomalies; large event infrastructure planning. On the other hand, high density crowds introduce novel problems to the detection task. First, clutter and occlusion problems are taken to the extreme, so that only heads are visible, and they are not easily separable from the moving background. Second, heads are usually small (they have a diameter of typically less than ten pixels) and with little or no textures. This comes out from two independent constraints, the need of one camera to have a field of view as high as possible, and the need of anonymization, i.e. the pedestrians must be not identifiable because of privacy concerns.In this work we develop a complete framework in order to handle the pedestrian detection and tracking problems under the presence of the novel difficulties that they introduce, by using multiple cameras, in order to implicitly handle the high occlusion issues.As a first contribution, we propose a robust method for camera pose estimation in surveillance environments. We handle problems as high distances between cameras, large perspective variations, and scarcity of matching information, by exploiting an entire video stream to perform the calibration, in such a way that it exhibits fast convergence to a good solution. Moreover, we are concerned not only with a global fitness of the solution, but also with reaching low local errors.As a second contribution, we propose an unsupervised multiple camera detection method which exploits the visual consistency of pixels between multiple views in order to estimate the presence of a pedestrian. After a fully automatic metric registration of the scene, one is capable of jointly estimating the presence of a pedestrian and its height, allowing for the projection of detections on a common ground plane, and thus allowing for 3D tracking, which can be much more robust with respect to image space based tracking.In the third part, we study different methods in order to perform supervised pedestrian detection on single views. Specifically, we aim to build a dense pedestrian segmentation of the scene starting from spatially imprecise labeling of data, i.e. heads centers instead of full head contours, since their extraction is unfeasible in a dense crowd. Most notably, deep architectures for semantic segmentation are studied and adapted to the problem of small head detection in cluttered environments.As last but not least contribution, we propose a novel framework in order to perform efficient information fusion in 2D spaces. The final aim is to perform multiple sensor fusion (supervised detectors on each view, and an unsupervised detector on multiple views) at ground plane level, that is, thus, our discernment frame. Since the space complexity of such discernment frame is very large, we propose an efficient compound hypothesis representation which has been shown to be invariant to the scale of the search space. Through such representation, we are capable of defining efficient basic operators and combination rules of Belief Function Theory. Furthermore, we propose a complementary graph based description of the relationships between compound hypotheses (i.e. intersections and inclusion), in order to perform efficient algorithms for, e.g. high level decision making.Finally, we demonstrate our information fusion approach both at a spatial level, i.e. between detectors of different natures, and at a temporal level, by performing evidential tracking of pedestrians on real large scale scenes in sparse and dense conditions
Al-nasur, Sadeq J. "New Models for Crowd Dynamics and Control." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/30107.
Повний текст джерелаPh. D.
Silva, Felipe Feliciano Gomes da. "Vibrações induzidas por multidões: efeito nos movimentos corpóreos dos pedestres na direção transversal." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/8979.
Повний текст джерелаMade available in DSpace on 2017-06-05T12:42:07Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3657172 bytes, checksum: 49a2dbaae14b810a2f42bd26d7f5f3db (MD5) Previous issue date: 2016-08-15
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
The analysis of the vibrations induced by crowds in the transverse direction has become a topic of increasing interest, because of the ocurrence of excessive transverse vibrations in certain structures due to pedestrian traffic. This work presents the analysis of movements of pedestrians in the transverse direction for crowd situations. Successive tests were carried out with persons instrumented, walking alone and in a crowd. Comparisons between measurements of these pedestrians walking alone and in the crowd provided the identification of the influence of the crowd in the transverse acceleration and displacements and rotation of the pelvis.
A análise de vibrações induzidas por multidões na direção transversal vem se tornando um tema cada vez de maior interesse devido a ocorrência de vibrações transversais excessivas em algumas estruturas destinas à circulação de pedestres. Este trabalho apresenta a análise de caminhadas/movimentos na direção transversal para situações de multidão. Para obtenção dos dados experimentais foram feitos testes sucessivos com pessoas instrumentadas, caminhando isoladamente e em meio a uma multidão com densidades diferentes. A análise comparativa dos sinais destes pedestres caminhando só e em multidão, possibilitou a identificação da influência causada por essa multidão na aceleração e deslocamento transversal e na rotação da pélvis.
Cabrero, Daniel Beatriz. "Automating crowd simulation: from parameter tuning to dynamic context-to-policy adaptation." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673251.
Повний текст джерелаLes multituds simulades per ordinador són cada cop més habituals en cinema, vídeo jocs i en aplicacions relacionades amb la seguretat. Existeixen molts algoritmes per simular multituds per adreçar tal varietat d’indústries. Tot i que els principis subjacents són similars, hi ha diferències entre les simulacions resultants. Cada algoritme té avantatges i inconvenients que s’han de valorar, i, a més a més, cal trobar valors pels seus paràmetres. Aquestes no són tasques senzilles i, sovint, es fan servir algoritmes d’aprenentatge automàtic per guiar aquestes decisions. Estudiem tres d’aquestes tasques: donar valor als paràmetres, avaluar trajectòries, i adaptar les polítiques. Els resultats demostren la utilitat dels mètodes proposats per avaluar trajectòries noves per tal de trobar valors apropiats pels paràmetres dels algorismes sense fer servir dades reals directament. A més a més, proposem una estratègia per adaptar la política de cada agent a través del reconeixement del context, millorant les simulacions.
Kabalan, Bachar. "Dynamique des foules : modélisation du mouvement des piétons et forces associées engendrées." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1126/document.
Повний текст джерелаCrowds are present almost everywhere and affect several aspects of our lives. They are considered to be on of the most complex systems whose dynamics, resulting from individual interactions and giving rise to fascinating phenomena, is very difficult to understand and have always intrigued experts from various domains. The technological advancement, especially in computer performance, has allowed to model and simulate pedestrian movement. Research from different disciplines, such as social sciences and bio-mechanics, who are interested in studying crowd movement and pedestrian interactions were able to better examine and understand the dynamics of the crowd. Professionals from architects and transport planners to fire engineers and security advisors are also interested in crowd models that would help them to optimize the design and operation of a facility. In this thesis, we have worked on the imporvement of a discrete crowd model developed by the researchers from the dynamics group in Navier laboratory. In this model, the actions and decisions taken by each individual are treated. In its previous version, the model was used to simulate urgent evacuations. Three main aspects of the model were addressed in this thesis. The first one concerns pedestrian navigation towards a final destination. In our model, a pedestrian is represented by a disk having a willingness to head to a certain destination with a desired direction and a desired speed. A desired direction is attributed to each pedestrian, depending on his position from the exit, from a floor field that is obtained by solving the eikonal equation. Solving this equation a single time at the beginning of the simulation or several times at during the simulation allows us to obtain the shortest path or the fastest path strategy respectively. The influence of the two strategies on the collective dynamics of the crowds is compared. The second one consists of managing pedestrian-pedestrian interactions. After having chosen his/her direction according to one of the available strategies, a pedestrian is bound to interact with other pedestrians present on the chosen path. We have integrated three pedestrian behaviors in our model: (i) pushing by using an original approach based on the theory of rigid body collisions in a rigorous thermodynamics context, (ii) forcing one's way by introducing a social repulsive force and (iii) "normal" avoidance by using a cognitive approach based on two heuristics. The three methods are compared for different criteria. The last aspect is the validation and verification of the model. We have performed a sensibility study and validated the model qualitatively and quantitatively. Using a numerical experimental plan, we identified the input parameters that are the most statistically significant and estimated the effects of their interactions. Concerning qualitative validation, we showed that our model is able to reproduce several self-organization phenomena such as lane formation. Finally, our model was validated quantitatively for the case of a bottleneck. The experimental results are very close to the ones obtained from simulations. The model was also applied to pedestrian movement in the Noisy-Champs train station. The objective of the study was to estimate the train dwell time. The simulation results were similar to the observations
Walker, Ross. "Autonomous robot navigation through a crowded and dynamic environment : using a novel form of path planning to demonstrate consideration towards pedestrians and other robots." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/18833/.
Повний текст джерелаPaganelli, Lorenzo. "Simulazione di evacuazione di folle in Alchemist: un modello di mappa mentale per pedoni cognitivi." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20540/.
Повний текст джерелаDu, Plessis Dewald. "APPOLO - Towards integrated urban education in Pretoria : a multi-functional vertical primary school." Diss., University of Pretoria, 2010. http://hdl.handle.net/2263/29976.
Повний текст джерелаMini Dissertation (MArch(Prof))--University of Pretoria, 2010.
Architecture
unrestricted
Johansson, Anders. "Data-Driven Modeling of Pedestrian Crowds." Doctoral thesis, 2008. https://tud.qucosa.de/id/qucosa%3A25055.
Повний текст джерелаAls diese Dissertation im Januar 2005 begonnen wurde, nutzten wissenschaftliche Untersuchungen von Fußgängern fast ausschließlich Computersimulationen und Evakuierungsexperimente. Seit dem haben viele Wissenschaftler an einer Verbesserung der Methoden gearbeitet. Heute werden empirische Daten mit Hilfe von Videoanalysen, Laser- und Infrarotkameras erhoben.Jedoch konzentrieren sich viele dieser Arbeiten auf künstliche Setups, in denen sich Fußgängermassen durch Korridore und Engpässe bewegen. Diese Experimente erlauben es, Massenbewegungen zu verstehen. Jedoch gibt es immer noch Forschungslücken. Es ist schwierig, unter solch kontrollierten Bedingungen Fortschritte darin zu erzielen, die auftretenden Dyamiken bei großen Katastrophen zu verstehen, in denen manchmal Hunderttausende oder sogar Millionen von Fußgängern involviert sind. Immer wieder kommt es zu Katastrophen in großen Menschenmengen. Leider sind von diesen Ereignissen häufig nur qualitative Informationen anstelle von quantitativen Daten erhältlich. Es ergab sich die besondere Gelegenheit, quantitatives Filmmaterial über eine Katastrophe in Mina (Königreich Saudi--Arabien) zu erhalten. Dort starben am 12. Januar 2006 hunderte von Pilgern während der jährlichen muslimischen Pilgerfahrt nach Mekka. Mit dem erhobenen Videomaterial konnte nachvollzogen werden, wie die Menschenmenge zuerst unbehindert fließen konnte, dann immer dichter wurde und wie es schließlich zur Katastrophe kam. Von den Erkenntnissen der Analyse der oben beschriebenen Katastrophe konnten neue Methoden entwickelt werden, die dabei helfen können, ähnliche Katastrophen in Zukunft zu vermeiden. Ein weiterer Beitrag dieser Dissertation besteht darin, einige Annahmen, die üblicherweise bei der Simulation von Fußgängerdynamiken gemacht werden, in Frage zu stellen und zu überarbeiten. Diese Annahmen sind: (1) Ein Fußgänger verhindert Zusammenstöße, indem er seine Schrittgeschwindigkeit so verändert, dass seine Beschleunigung exponentiell mit der Distanz zu dem zu umgehenden Fußgänger oder Objekt abnimmt. (2) Ein Fußgänger zeigt stärkere Reaktionen auf Ereignisse, die vor ihm passieren, als auf Ereignisse, die hinter ihm passieren. (3) Die Bewegung eines in einer Menschenmenge befindlichen Fußgängers folgt immer dem Strömungs--Dichte Verhältnis, was als Fundamental-Diagramm bezeichnet wird. (4) Die Laufgeschwindigkeit eines Fußgängers erreicht bei maximaler Menschendichte einem Wert von 0 m/s. Die ersten beiden Annahmen wurden von den empirischen Daten bestätigt. Unsere Analysen zeigen jedoch, dass die Annahmen 3 und 4 nicht immer gültig sind. Somit müssen Standardtheorien von Fußgängerdynamiken überarbeitet werden. Im Anschluß an die Analyse dieser fundamentalen Aspekte von Fußgängerverhalten und dem Verhalten bei Ausweichmanövern wird das Social-Force-Modell weiterentwickelt. Um auf vorhergehenden Arbeiten aufzubauen und um die oben beschriebene Katastrophe analysieren zu können, werden Algorithmen für die Video-Verfolgung von Fußgängerbewegungen entwickelt. Das Neue bei diesem Teil der Arbeit liegt nicht nur in dem verwendeten Verfahren selbst, sondern auch in der Einzigartigkeit und der großen Menge an verwendeten Daten, die mit diesem Verfahren analysiert werden. Ein zentrales Ziel dieser Arbeit besteht demnach in einer wissenschaftlichen Weiterentwicklung von theoretischen Modellen und kontrollierten Laborexperimenten hin zu Modellen, die unter realen Bedingungen tatsächlich anwendbar sind. Die Analyse von Fußgängern ist ein interdisziplinäres Feld, das von verschiedenen wissenschaftlichen Disziplinen mit verschiedenen Zielen betrieben wird. Leider gab es bislang wenig Bemühungen, die Resultate innerhalb dieser Teilgebiete im Rahmen einer konsistenten Theorie zu vereinen. Als seltene Ausnahmen können die Arbeiten von Teknomo und Antonini genannt werden. Diese Dissertation verfolgt das Ziel, diese theoretische Vereinigung weiter voran zu treiben. Dazu muss man zwischen der Neuerfindung des Rades und der Wiederverwendung nicht geprüfter Resultate abwägen. Dementsprechend ist ein Teil dieser Dissertation dem Vorhaben gewidmet, bisherige Forschung im Lichte empirischer Daten und neuer Methoden zu evaluieren. Da sich die Arbeit mit recht unterschiedlichen Aspekten von Fußgängerverhalten beschäftigt, konzentriert sich die Analyse in verschiedenen Teilen der Arbeit auf einige ausgewählte, alternative Modelle. Insbesondere bei der Modellierung und Simulation wird anstelle einer eingehenden Übersicht verschiedener Modelle eine Diskussion des speziellen Social-Force Modells präsentiert.
"Pedestrian Behavior Modeling and Understanding in Crowds." 2016. http://repository.lib.cuhk.edu.hk/en/item/cuhk-1292603.
Повний текст джерелаChen, Shiang-yu, and 陳相宇. "Simulating Pedestrian Crowds in Smoky Emergency Situations." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/47401495338216617404.
Повний текст джерела大同大學
資訊工程學系(所)
96
Crowd animation is often appearance in recent movie scenes. It can be realistic. Simulating behaviors and motion of people in emergency situations for safety systems has been widely studied recently. In this simulation, we simulate the crowd of pedestrians. Behaviors of people in emergency can be simulated by the system. When an architect designs the safety systems, how to set the safety equipment and, how to design the path of escaping from panic is an important problem. This system is based on a well known physics-based animation model which allows to consider influence of gaseous phenomena such as smoke in the behavior of the crowd. We simulate a normal public place, with the safety be set at the exits and paths. We can observe the effect of the smoke to the guiding lights received by pedestrians in this simulation.
Johansson, Anders Fredrik [Verfasser]. "Data-driven modeling of pedestrian crowds / by Anders Fredrik Johansson." 2009. http://d-nb.info/1007304812/34.
Повний текст джерелаAlrashed, Mohammed. "Agent Based Modeling and Simulation of Pedestrian Crowds In Panic Situations." Thesis, 2016. http://hdl.handle.net/10754/621941.
Повний текст джерелаKhandelwal, Tarun. "Activity-travel behavior modeling of pilgrims in mass religious gatherings." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5660.
Повний текст джерелаLin, You-Kang, and 林祐綱. "Counting Pedestrians in Crowds under Occlusions." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/71675718811723575015.
Повний текст джерела元智大學
電機工程學系
97
It’s difficult to segment and count people in occlusion. This problem has been an important task for a long time. Usually, we propose some hypotheses to simplify the problem of counting people in crowded. For example, the camera must be set the higher place top of humans. Therefore, the occlusion event between people will be simplified to blob merge and split. The problem of occlusion which far objects cover with near objects will be not produced. On the other hand, we can use multi cameras to surveillance the area which has overlap region between cameras. Then, use different information of cameras to make up for the problem of information is not enough in single camera. But those supposes are not suitable in real work. So, this thesis will count people under normal camera (one camera in side-view). This thesis uses contour matching to complete people counting quickly. It also uses markov chain monte carlo method to do the follow-up procedure of template matching. Finally, we use the result of template matching to create new contour model on-line.
Haji, Ali Abdul Lateef. "Pedestrian Flow in the Mean Field Limit." Thesis, 2012. http://hdl.handle.net/10754/250912.
Повний текст джерелаYU, SHU-HAN, and 虞宗翰. "Pedestrian Re-Identification and Crowd Tracking Using Convolutional Neural Networks." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9972dw.
Повний текст джерела國立臺北大學
資訊工程學系
107
Plenty of surveillance cameras were installed in several public areas,the camera video stream control monitoring system can assist in maintaining safety at the site to prevent criminal activities . Without a surveillance camera system, a large number of human patrols or guards must be arranged to achieve the same level of monitoring, which will increase personnel and logistical costs. This study proposes a method for pedestrian re-identification and crowd tracking, using computer vision techniques to detect targets from different camera views and angles, as well as identifying and tracking pedestrians or populations and calculating the number of people. We use Mask R-CNN to detect pedestrians. Based on the results of the detection, tracking is performed using the IOU-tracker. The tracking results are compared using a batch-feature- erasing-network to confirm the similarity between data from different cameras. The crowd is defined by the results of re-identification, after which it is tracked and counted, and finally, re-identification and tracking is fully achieved using this method. The method shows good results with the Duke dataset.
Chen, Chun-Yuan, and 陳俊元. "Crowded Pedestrian Detection Using EM based on Weighted Local Features." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/49492808863148476349.
Повний текст джерела國立高雄第一科技大學
電腦與通訊工程研究所
102
Pedestrian detection and counting is an important topic in developing an intelligent surveillance system. In this work, we propose a vision-based system for detecting pedestrians in an image. Be robust to crowded scenes and adapt to incomplete foreground from background subtraction algorithm, expectation maximization (EM) algorithm is applied to impose the constraint of body part for achieving successful detection. First, the corner points at body part are all detected and described using histogram of oriented gradients (HOGs). In addition, one of three body part labels (head, torso, and leg), a kind of locality property, is encoded in corner points for overcoming the mutual occlusion situation. Then, we apply a grouping algorithm in HOGs feature space to form a set of clusters. Each cluster center is considered as a code word and the probabilities of this cluster belonging to head, torso, or leg are also computed, respectively. During detecting phase, all detected corner points are matched to the construct code words and are assigned to three body part probabilities. After that, an EM algorithm is applied to iteratively estimate the likelihood probability of all corner points to the pedestrian candidates (E-Step) and update the parameters of the pedestrian models (M-Step). In the experiment, three videos are used to validate the performance of the proposed method.
Chen, Yao-Hsiang, and 陳耀祥. "Crowded Pedestrian Detection Using EM based on Multi-level HOGs of Body Parts." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/25720267977881339799.
Повний текст джерела國立高雄第一科技大學
電腦與通訊工程研究所
103
This paper proposes a vision-based method for detecting pedestrians from crowded scenes. To address occlusion problem faced in crowded pedestrian detection, this paper models the pedestrian appearance by equally dividing a pedestrian into eight body patches. Each patch is described by using multi-level histogram of oriented gradients (ML-HOGs) and then a support vector machine (SVM) is learned for determining its existence. By parameterizing the pedestrians to be detected, the problem of crowded pedestrian detection is formulated as the parameter estimation one. A statistical way to solve this problem is by maximizing likelihood (ML) probability. A well-known algorithm called expectation maximization (EM) is applied to achieve the solution in case of missing data due to occlusion in crowded scenes. The EM algorithm firstly generates a set of initial pedestrian hypothesis by using the learned eight SVMs to detect the patches with high possibility belonging to the head through voting mechanism. After that, EM algorithm iteratively estimates the likelihood probability of all pixels with respect to the pedestrian hypothesis (E-step) and then updates their parameters (M-step) until it reaches the convergence condition. Finally, the false and redundant hypothesis from EM algorithm are removed through the proposed verification steps. In the experiment, the videos from CAVIAR datasets are used for validating the proposed method.
Yaghoubi, Ehsan. "Soft Biometric Analysis: MultiPerson and RealTime Pedestrian Attribute Recognition in Crowded Urban Environments." Doctoral thesis, 2021. http://hdl.handle.net/10400.6/12081.
Повний текст джерелаThis thesis was prepared at the University of Beria Interior, IT Instituto de Telecomunicações, Soft Computing and Image Analysis Laboratory (SOCIA Lab), Covilhã Delegation, and was submitted to the University of Beira Interior for defense in a public examination session.
Liang, Chih-Bin, and 梁志彬. "A Vision-based Detection System for Walking-cross Activities of Pedestrians." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/18872406598533197589.
Повний текст джерела淡江大學
土木工程學系
85
In this thesis, we try to use image processing technique to count pedestrians which are stationary in the image and track their trajectories when they are walking. In the pedestrian counting system, since the pixels which pedestrian possesses in the image are directly proportional to number of pedestrians, so we use background differencing method to establish regression model and calculate all people in the image. On the other hand, we use interframe differencing method to establish another regression model which is used to calculate moving pedestrians in the image. The difference between total number of pedestrians and number of moving pedestrians at the same time is considered to be the number of stationary pedestrians in the image. About pedestrian''s trajectory detection, we adopt template matching method based on image feature invariants to track each pedestrian''s template in sequence images. After linking every coordinates, we obtain pedestrians'' trajectory lines. The detection system can output four important parameters including pedestrians'' number, trajectories, speeds, and directions. A case study was demonstrated. About stationary pedestrians, the absolute diffenence between automaticcounts and real counts for each image is almost within 2 persons, and the ratio of maximum absolute error to the real count decrease gradually when people increase. About trajectory, the use of template matching method have only an average error of 1 pixel in x-axis, 2 pixel in y-axis. The error of speed is about 9.43%.
Alrashed, Mohammed. "Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management." Diss., 2020. http://hdl.handle.net/10754/665965.
Повний текст джерела