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View-dependent adaptive cloth simulation
This paper describes a method for view-dependent cloth simulation using dynamically adaptive mesh refinement and coarsening. Given a prescribed camera motion, the method adjusts the criteria controlling refinement to account for visibility and apparent size in the camera's view. Objectionable dynamic artifacts are avoided by anticipative refinement and smoothed coarsening. This approach preserves the appearance of detailed cloth throughout the animation while avoiding the wasted effort of simulating details that would not be discernible to the viewer. The computational savings realized by this method increase as scene complexity grows, producing a 2Ă speed-up for a single character and more than 4Ă for a small group
Real-time biped character stepping
PhD ThesisA rudimentary biped activity that is essential in interactive evirtual worlds, such as
video-games and training simulations, is stepping. For example, stepping is fundamental in everyday terrestrial activities that include walking and balance recovery.
Therefore an eïŹective 3D stepping control algorithm that is computationally fast
and easy to implement is extremely valuable and important to character animation
research. This thesis focuses on generating real-time controllable stepping motions
on-the-ïŹy without key-framed data that are responsive and robust (e.g.,can remain
upright and balanced under a variety of conditions, such as pushes and dynami-
cally changing terrain). In our approach, we control the characterâs direction and
speed by means of varying the stepposition and duration. Our lightweight stepping
model is used to create coordinated full-body motions, which produce directable
steps to guide the character with speciïŹc goals (e.g., following a particular path
while placing feet at viable locations). We also create protective steps in response
to random disturbances (e.g., pushes). Whereby, the system automatically calculates where and when to place the foot to remedy the disruption. In conclusion,
the inverted pendulum has a number of limitations that we address and resolve
to produce an improved lightweight technique that provides better control and
stability using approximate feature enhancements, for instance, ankle-torque and
elongated-body
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Computational Methods for Cognitive and Cooperative Robotics
In the last decades design methods in control engineering made substantial progress in
the areas of robotics and computer animation. Nowadays these methods incorporate the
newest developments in machine learning and artificial intelligence. But the problems
of flexible and online-adaptive combinations of motor behaviors remain challenging for
human-like animations and for humanoid robotics. In this context, biologically-motivated
methods for the analysis and re-synthesis of human motor programs provide new insights
in and models for the anticipatory motion synthesis.
This thesis presents the authorâs achievements in the areas of cognitive and developmental robotics, cooperative and humanoid robotics and intelligent and machine learning methods in computer graphics. The first part of the thesis in the chapter âGoal-directed Imitation for Robotsâ considers imitation learning in cognitive and developmental robotics.
The work presented here details the authorâs progress in the development of hierarchical
motion recognition and planning inspired by recent discoveries of the functions of mirror-neuron cortical circuits in primates. The overall architecture is capable of âlearning for
imitationâ and âlearning by imitationâ. The complete system includes a low-level real-time
capable path planning subsystem for obstacle avoidance during arm reaching. The learning-based path planning subsystem is universal for all types of anthropomorphic robot arms, and is capable of knowledge transfer at the level of individual motor acts.
Next, the problems of learning and synthesis of motor synergies, the spatial and spatio-temporal combinations of motor features in sequential multi-action behavior, and the
problems of task-related action transitions are considered in the second part of the thesis
âKinematic Motion Synthesis for Computer Graphics and Roboticsâ. In this part, a new
approach of modeling complex full-body human actions by mixtures of time-shift invariant
motor primitives in presented. The online-capable full-body motion generation architecture
based on dynamic movement primitives driving the time-shift invariant motor synergies
was implemented as an online-reactive adaptive motion synthesis for computer graphics
and robotics applications.
The last chapter of the thesis entitled âContraction Theory and Self-organized Scenarios
in Computer Graphics and Roboticsâ is dedicated to optimal control strategies in multi-agent scenarios of large crowds of agents expressing highly nonlinear behaviors. This last
part presents new mathematical tools for stability analysis and synthesis of multi-agent
cooperative scenarios.In den letzten Jahrzehnten hat die Forschung in den Bereichen der Steuerung und Regelung
komplexer Systeme erhebliche Fortschritte gemacht, insbesondere in den Bereichen
Robotik und Computeranimation. Die Entwicklung solcher Systeme verwendet heutzutage
neueste Methoden und Entwicklungen im Bereich des maschinellen Lernens und der
kĂŒnstlichen Intelligenz. Die flexible und echtzeitfĂ€hige Kombination von motorischen Verhaltensweisen
ist eine wesentliche Herausforderung fĂŒr die Generierung menschenĂ€hnlicher
Animationen und in der humanoiden Robotik. In diesem Zusammenhang liefern biologisch
motivierte Methoden zur Analyse und Resynthese menschlicher motorischer Programme
neue Erkenntnisse und Modelle fĂŒr die antizipatorische Bewegungssynthese.
Diese Dissertation prÀsentiert die Ergebnisse der Arbeiten des Autors im Gebiet der
kognitiven und Entwicklungsrobotik, kooperativer und humanoider Robotersysteme sowie
intelligenter und maschineller Lernmethoden in der Computergrafik. Der erste Teil der
Dissertation im Kapitel âZielgerichtete Nachahmung fĂŒr Roboterâ behandelt das Imitationslernen
in der kognitiven und Entwicklungsrobotik. Die vorgestellten Arbeiten beschreiben
neue Methoden fĂŒr die hierarchische Bewegungserkennung und -planung, die durch
Erkenntnisse zur Funktion der kortikalen Spiegelneuronen-Schaltkreise bei Primaten inspiriert
wurden. Die entwickelte Architektur ist in der Lage, âdurch Imitation zu lernenâ
und âzu lernen zu imitierenâ. Das komplette entwickelte System enthĂ€lt ein echtzeitfĂ€higes
Pfadplanungssubsystem zur Hindernisvermeidung wĂ€hrend der DurchfĂŒhrung von Armbewegungen.
Das lernbasierte Pfadplanungssubsystem ist universell und fĂŒr alle Arten von
anthropomorphen Roboterarmen in der Lage, Wissen auf der Ebene einzelner motorischer
Handlungen zu ĂŒbertragen.
Im zweiten Teil der Arbeit âKinematische Bewegungssynthese fĂŒr Computergrafik und
Robotikâ werden die Probleme des Lernens und der Synthese motorischer Synergien, d.h.
von rÀumlichen und rÀumlich-zeitlichen Kombinationen motorischer Bewegungselemente
bei Bewegungssequenzen und bei aufgabenbezogenen Handlungs ĂŒbergĂ€ngen behandelt.
Es wird ein neuer Ansatz zur Modellierung komplexer menschlicher Ganzkörperaktionen
durch Mischungen von zeitverschiebungsinvarianten Motorprimitiven vorgestellt. Zudem
wurde ein online-fĂ€higer Synthesealgorithmus fĂŒr Ganzköperbewegungen entwickelt, der
auf dynamischen Bewegungsprimitiven basiert, die wiederum auf der Basis der gelernten
verschiebungsinvarianten Primitive konstruiert werden. Dieser Algorithmus wurde fĂŒr
verschiedene Probleme der Bewegungssynthese fĂŒr die Computergrafik- und Roboteranwendungen
implementiert.
Das letzte Kapitel der Dissertation mit dem Titel âKontraktionstheorie und selbstorganisierte
Szenarien in der Computergrafik und Robotikâ widmet sich optimalen Kontrollstrategien
in Multi-Agenten-Szenarien, wobei die Agenten durch eine hochgradig nichtlineare
Kinematik gekennzeichnet sind. Dieser letzte Teil prÀsentiert neue mathematische Werkzeuge
fĂŒr die StabilitĂ€tsanalyse und Synthese von kooperativen Multi-Agenten-Szenarien
Public Security vs. Private Self-Protection: Optimal Taxation and the Social Dynamics of Fear
In this paper, we develop a simple model of social dynamics governing the evolution of strategic self-protection choices of boundedly rational potential victims facing the threat of prospective offenders in a large population with random matching. We prove that individual (and socially transmitted) fear of exposure to criminal threats may actually condition choices even in the face of objective evidence of declining crime rates, and thereby cause the eventual selection of Pareto inefficient equilibria with self-protection. We also show that a suitable strategy of provision of public security financed through discriminatory taxation of self-protective expenses may actually overcome this problem, and drive the social dynamics toward the efficient no protection equilibrium. In our model, we do not obtain, as in Cressman et al. (1998), a crowding-out result such that the net impact of public spending on the actual social dynamics is neutral and the economy keeps on cycling between phases of high and low criminal activity with varying levels of self-protection; quite to the contrary, it can be extremely effective in implementing the social optimum, in that it acts primarily on the intangible dimension, that is, on the social dynamics of fear. We claim that this kind of result calls for more interdisciplinary research on the socio-psycho-economic determinants of fear of crime, and for consequent advances in modelling approaches and techniques.Self-Protection, Fear of Crime, Cultural Selection Dynamics, Replicator Dynamics
Visualizing the Motion Flow of Crowds
In modern cities, massive population causes problems, like congestion, accident, violence and crime everywhere. Video surveillance system such as closed-circuit television cameras is widely used by security guards to monitor human behaviors and activities to manage, direct, or protect people. With the quantity and prolonged duration of the recorded videos, it requires a huge amount of human resources to examine these video recordings and keep track of activities and events. In recent years, new techniques in computer vision field reduce the barrier of entry, allowing developers to experiment more with intelligent surveillance video system. Different from previous research, this dissertation does not address any algorithm design concerns related to object detection or object tracking. This study will put efforts on the technological side and executing methodologies in data visualization to find the model of detecting anomalies. It would like to provide an understanding of how to detect the behavior of the pedestrians in the video and find out anomalies or abnormal cases by using techniques of data visualization
Privacy in Public and the contextual conditions of agency
Current technology and surveillance practices make behaviors traceable to persons in unprecedented ways. This causes a loss of anonymity and of many privacy measures relied on in the past. These de facto privacy losses are by many seen as problematic for individual psychology, intimate relations and democratic practices such as free speech and free assembly. I share most of these concerns but propose that an even more fundamental problem might be that our very ability to act as autonomous and purposive agents relies on some degree of privacy, perhaps particularly as we act in public and semi-public spaces. I suggest that basic issues concerning action choices have been left largely unexplored, due to a series of problematic theoretical assumptions at the heart of privacy debates. One such assumption has to do with the influential conceptualization of privacy as pertaining to personal intimate facts belonging to a private sphere as opposed to a public sphere of public facts. As Helen Nissenbaum has pointed out, the notion of privacy in public sounds almost like an oxymoron given this traditional private-public dichotomy. I discuss her important attempt to defend privacy in public through her concept of âcontextual integrity.â Context is crucial, but Nissenbaumâs descriptive notion of existing norms seems to fall short of a solution. I here agree with Joel Reidenbergâs recent worries regarding any approach that relies on âreasonable expectationsâ . The problem is that in many current contexts we have no such expectations. Our contexts have already lost their integrity, so to speak. By way of a functional and more biologically inspired account, I analyze the relational and contextual dynamics of both privacy needs and harms. Through an understanding of action choice as situated and options and capabilities as relational, a more consequence-oriented notion of privacy begins to appear. I suggest that privacy needs, harms and protections are relational. Privacy might have less to do with seclusion and absolute transactional control than hitherto thought. It might instead hinge on capacities to limit the social consequences of our actions through knowing and shaping our perceptible agency and social contexts of action. To act with intent we generally need the ability to conceal during exposure. If this analysis is correct then relational privacy is an important condition for autonomic purposive and responsible agencyâparticularly in public space. Overall, this chapter offers a first stab at a reconceptualization of our privacy needs as relational to contexts of action. In terms of ârights to privacyâ this means that we should expand our view from the regulation and protection of the information of individuals to questions of the kind of contexts we are creating. I am here particularly interested in what I call âunbounded contextsâ, i.e. cases of context collapses, hidden audiences and even unknowable future agents
Dispositions for Christian Witness Among Theravada Buddhists
This article reflects on communicating the Christian gospel appropriately and effectively among Southeast Asian Theravada Buddhists (SEATB). It is concerned with contextualizing the means of communication rather than theological concepts. Contextualization is often discussed with little reference to the level of contextualization, including: the content of the gospel, liturgical forms, social rules for relating, and dispositions shaped by Buddhist virtues used in communication. Examples are given of contextualization among SEATB, and then descriptions of how communicators of the gospel can use dispositions shaped by key Buddhist virtues. An argument is made that among SEATB, the means of communicating the gospel is often far more important than the content of the gospel. This suggests that communicators of the gospel would do well to become competent in communicating in ways that reflect the local rules for relationships and by appropriating nonverbals that communicate dispositions of Buddhist virtue
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