A person's emotions and state of mind are apparent in their face and eyes. As a Latin proverb states: ‘The face is the portrait of the mind; the eyes, its informers’. This presents a significant ...challenge for Computer Graphics researchers who generate artificial entities that aim to replicate the movement and appearance of the human eye, which is so important in human–human interactions. This review article provides an overview of the efforts made on tackling this demanding task. As with many topics in computer graphics, a cross‐disciplinary approach is required to fully understand the workings of the eye in the transmission of information to the user. We begin with a discussion of the movement of the eyeballs, eyelids and the head from a physiological perspective and how these movements can be modelled, rendered and animated in computer graphics applications. Furthermore, we present recent research from psychology and sociology that seeks to understand higher level behaviours, such as attention and eye gaze, during the expression of emotion or during conversation. We discuss how these findings are synthesized in computer graphics and can be utilized in the domains of Human–Robot Interaction and Human–Computer Interaction for allowing humans to interact with virtual agents and other artificial entities. We conclude with a summary of guidelines for animating the eye and head from the perspective of a character animator.
A person's emotions and state of mind are apparent in their face and eyes. As a Latin proverb states: ‘The face is the portrait of the mind; the eyes, its informers’. This presents a significant challenge for Computer Graphics researchers who generate artificial entities that aim to replicate the movement and appearance of the human eye, which is so important in human–human interactions. This review article provides an overview of the efforts made on tackling this demanding task. As with many topics in computer graphics, a cross‐disciplinary approach is required to fully understand the workings of the eye in the transmission of information to the user.
In this paper we develop a set of inverse kinematics algorithms suitable for an anthropomorphic arm or leg. We use a combination of analytical and numerical methods to solve generalized inverse ...kinematics problems including position, orientation, and aiming constraints. Our combination of analytical and numerical methods results in faster and more reliable algorithms than conventional inverse Jacobian and optimization-based techniques. Additionally, unlike conventional numerical algorithms, our methods allow the user to interactively explore all possible solutions using an intuitive set of parameters that define the redundancy of the system.
Eyes alive Lee, Sooha Park; Badler, Jeremy B.; Badler, Norman I.
ACM transactions on graphics,
07/2002, Letnik:
21, Številka:
3
Journal Article
Recenzirano
For an animated human face model to appear natural it should produce eye movements consistent with human ocular behavior. During face-to-face conversational interactions, eyes exhibit conversational ...turn-taking and agent thought processes through gaze direction, saccades, and scan patterns. We have implemented an eye movement model based on empirical models of saccades and statistical models of eye-tracking data. Face animations using stationary eyes, eyes with random saccades only, and eyes with statistically derived saccades are compared, to evaluate whether they appear natural and effective while communicating.
A simple inverse kinematics procedure is proposed for a seven degree of freedom model of the human arm. Two schemes are used to provide an additional constraint leading to closed-form analytical ...equations with an upper bound of two or four solutions. Multiple solutions can be evaluated on the basis of their proximity from the rest angles or the previous configuration of the arm. Empirical results demonstrate that the procedure is well suited for real-time applications.
Generating Facial Expressions for Speech Pelachaud, Catherine; Badler, Norman I.; Steedman, Mark
Cognitive science,
January 1996, 1996, 1996-01-00, 19960101, Letnik:
20, Številka:
1
Journal Article
Recenzirano
Odprti dostop
This article reports results from a program that produces high‐quality animation of facial expressions and head movements as automatically as possible in conjunction with meaning‐based speech ...synthesis, including spoken intonation. The goal of the research is as much to test and define our theories of the formal semantics for such gestures, as to produce convincing animation. Towards this end, we have produced a high‐level programming language for three‐dimensional (3‐D) animation of facial expressions. We have been concerned primarily with expressions conveying information correlated with the intonation of the voice: This includes the differences of timing, pitch, and emphasis that are related to such semantic distinctions of discourse as “focus,”“topic,” and “comment,”“theme” and “rheme,” or “given” and “new” information. We are also interested in the relation of affect or emotion to facial expression. Until now, systems have not embodied such rule‐governed translation from spoken utterance meaning to facial expressions. Our system embodies rules that describe and coordinate these relations: intonation/information, intonation/affect, and facial expressions/affect. A meaning representation includes discourse information: What is contrastive/background information in the given context, and what is the “topic” or “theme” of the discourse? The system maps the meaning representation into how accents and their placement are chosen, how they are conveyed over facial expression, and how speech and facial expressions are coordinated. This determines a sequence of functional groups: lip shapes, conversational signals, punctuators, regulators, and manipulators. Our algorithms then impose synchrony, create coarticulation effects, and determine affectual signals, eye and head movements. The lowest level representation is the Facial Action Coding System (FACS), which makes the generation system portable to other facial models.
An articulated figure is often modeled as a set of rigid segments connected with joints. Its configuration can be altered by varying the joint angles. Although it is straight forward to compute ...figure configurations given joint angles (forward kinematics), it is more difficult to find the joint angles for a desired configuration (inverse kinematics). Since the inverse kinematics problem is of special importance to an animator wishing to set a figure to a posture satisfying a set of positioning constraints, researchers have proposed several different approaches. However, when we try to follow these approaches in an interactive animation system where the object on which to operate is as highly articulated as a realistic human figure, they fail in either generality or performance. So, we approach this problem through nonlinear programming techniques. It has been successfully used since 1988 in the spatial constraint system within
Jack
, a human figure simulation system developed at the University of Pennsylvania, and proves to be satisfactorily efficient, controllable, and robust. A spatial constraint in our system involves two parts: one constraint on the figure, the
end-effector
, and one on the spatial environment, the
goal
. These two parts are dealt with separately, so that we can achieve a neat modular implementation. Constraints can be added one at a time with appropriate weights designating the importance of this constraint relative to the others and are always solved as a group. If physical limits prevent satisfaction of all the constraints, the system stops with the (possibly local) optimal solution for the given weights. Also, the rigidity of each joint angle can be controlled, which is useful for redundant degrees of freedom.
This paper presents a neural computing model that can automatically extract motion qualities from live performance. The motion qualities are in terms of laban movement analysis (LMA) Effort factors. ...The model inputs both 3D motion capture and 2D video projections. The output is a classification of motion qualities that are detected in the input. The neural nets are trained with professional LMA notators to ensure valid analysis and have achieved an accuracy of about 90% in motion quality recognition. The combination of this system with the EMOTE motion synthesis system provides a capability for automating both observation and analysis processes, to produce natural gestures for embodied communicative agents.
This research proposes a computational framework for generating visual attending behavior in an embodied simulated human agent. Such behaviors directly control eye and head motions, and guide other ...actions such as locomotion and reach. The implementation of these concepts, referred to as the AVA, draws on empirical and qualitative observations known from psychology, human factors and computer vision. Deliberate behaviors, the analogs of scanpaths in visual psychology, compete with involuntary attention capture and lapses into idling or free viewing. Insights provided by implementing this framework are: a defined set of parameters that impact the observable effects of attention, a defined vocabulary of looking behaviors for certain motor and cognitive activity, a defined hierarchy of three levels of eye behavior (endogenous, exogenous and idling) and a proposed method of how these types interact.
With teleoperation being the contemporary standard for Human Robot Interaction (HRI), research into multi-modal communication (MMC) has focused on development of advanced Operator Control Units (OCU) ...supporting control of one or more robots. However, with advances being made to improve the perception, intelligence, and mobility of robots, a need exists to revolutionize the ways in which Soldiers interact with robotic team members. Within this future vision, mixed-initiative Soldier-Robot (SR) teams will work collaboratively sharing information back-and-forth in a fluid natural manner using combinations of communication methods. Therefore, new definitions are required to focus research efforts to support next-generation MMC. After a thorough survey of the literature and a scientific workshop on the topic, this paper aims to operationally define MMC, Explicit Communication, and Implicit Communication to encompass the shifting paradigm of HRI from a controller/controlled relationship to a cooperative team mate relationship. This paper presents the results from a survey of the literature and a scientific workshop that inform proposed definitions for multi-modal, explicit, and implicit communication. An illustrative scenario vignette provides context and specific examples of each communication type. Finally, future research efforts are summarized.
We present a model-based method for the multi-level shape, pose estimation and abstraction of an object's surface from range data. The surface shape is estimated based on the parameters of a ...superquadric that is subjected to global deformations (tapering and bending) and a varying number of levels of local deformations. Local deformations are implemented using locally adaptive finite elements whose shape functions are piecewise cubic functions with C^sup 1^ continuity. The surface pose is estimated based on the model's translational and rotational degrees of freedom. The algorithm first does a coarse fit, solving for a first approximation to the translation, rotation and global deformation parameters and then does several passes of mesh refinement, by locally subdividing triangles based on the distance between the given datapoints and the model. The adaptive finite element algorithm ensures that during subdivision the desirable finite element mesh generation properties of conformity, non-degeneracy and smoothness are maintained. Each pass of the algorithm uses physics-based modeling techniques to iteratively adjust the global and local parameters of the model in response to forces that are computed from approximation errors between the model and the data. We present results demonstrating the multi-level shape representation for both sparse and dense range data.PUBLICATION ABSTRACT
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