“Is It Within My Reach?” – An Agents Perspective

Huang, Zhisheng; Eliëns, Anton; Visser, Cees

doi:10.1007/978-3-540-39396-2_24

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…The VRML based DLP + X3D platform was used to create the environment, and the DLP + X3D/STEP agent platform to create interface characters that move naturally and use complex gestures (Eliëns et al, 2002). For more technical details, we refer to Huang et al (2003).…”

Section: Virtual Environmentmentioning

confidence: 99%

Realism is not all! User engagement with task-related interface characters

Vugt

Konijn

Hoorn

et al. 2007

Interacting with Computers

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Human-like characters in the interface may evoke social responses in users, and literature suggests that realism is the most important factor herein. However, the effects of interface characters on the user are not well understood. We developed an integrative framework, called I-PEFiC, to explain 'persona' and realism effects on the user. We tested an important part of the model using an experimental design in which 140 middle school students were class-wise shown an informative virtual reality demonstration that incorporated either a realistic or an unrealistic (fantasy) interface character, or no character. Findings show, first, no persona effect on task performance. We discuss how user engagement might be related to persona effects. Second, designed realism of the interface character contributed to user engagement when controlled for various user perceptions. Moreover, perceived aesthetics and task-relevance further influenced user engagement. Third, user engagement and task performance combined better predicted satisfaction than either one of the factors alone. In sum, several appearance-and task-related factors contributed to user engagement and user satisfaction. Thus, realism is not all.

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Section: Virtual Environmentmentioning

confidence: 99%

Realism is not all! User engagement with task-related interface characters

Vugt

Konijn

Hoorn

et al. 2007

Interacting with Computers

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“…Improving virtual humans in movements carried out in their individual 4 workspace is a classic problem (Huang et al, 2003;Zhao et al, 2005). We put the focus of this chapter on two issues of this challenge.…”

Section: Introductionmentioning

confidence: 99%

A computational model of cooperative spatial behaviour for virtual humans*

Nguyen¹,

Wachsmuth²

2013

Representing Space in Cognition

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This chapter introduces a model which connects representations of the space surrounding a virtual humanoid's body with the space it shares with several interaction partners. This work intends to support virtual humans (or humanoid robots) in near space interaction and is inspired by studies from cognitive neurosciences on the one hand and social interaction studies on the other hand. We present our work on learning the body structure of an articulated virtual human by using data from virtual touch and proprioception sensors. The results are utilized for a representation of its reaching space, the so-called peripersonal space, a concept known from cognitive neuroscience.In interpersonal interaction involving several partners, their peripersonal spaces may overlap and establish a shared reaching space. We define it as their interaction space, where cooperation takes place and where actions to claim or release spatial areas have to be adapted, to avoid obstructions of the other's movements. Our model of interaction space is developed as an extension of Kendon's F-formation system, a foundational theory of how humans orient themselves in space when communicating. Thus, interaction space allows for measuring not only the spatial arrangement (i.e., body posture and orientation) between multiple interaction partners, but also the extent of space they share. Peripersonal and interaction space are modeled as potential fields to control the virtual human's behaviour strategy. As an example we show how the virtual human can relocate object positions toward or away from locations reachable for all partners, and thus facilitating cooperation in an interaction task. In this chapter we shall demonstrate how a virtual human can cooperate with a partner in building a toy tower together, as one aspect of computationally modelling shared space and spatial behaviour for action coordination. Virtual humans are autonomous agents with human-like appearance and usually human-like multi-modal behaviour like speech, gaze, gestures, and facial expressions. In three-dimensional virtual reality environments, virtual humans can interact with other virtual humans or with real humans. For example, virtual humans like Max (Kopp et al., 2003) can act as co-situated guides in a construction task, or Steve (Rickel and Johnson, 2000), who act as tutors demonstrating physical tasks to students.In the mentioned scenarios, overlapping workspaces were usually avoided by maintaining enough distance between the partners to avoid interferences between their movements. We believe that in natural interaction such interferences have to be dealt with to accomplish cooperative interaction tasks. Thus, we present our work on modelling a virtual human's spatial behaviour in shared near space interactions in order to facilitate the accomplishment of and the partner's engagement in the cooperative task.Spatial interaction in tasks carried out in distances near to the agent's body usually pose a great challenge to virtual humans. In contrast, humans seem to...

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“…To our knowledge, work on learning reaching space for embodied agents has yet been done isolated from body schema acqusition ( [7], [4]). So far, this topic has been dominated by robotics researchers in order to build adaptive body schemas.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Modeling Peripersonal Action Space for Virtual Humans Using Touch and Proprioception

Nguyen

Wachsmuth

2009

Intelligent Virtual Agents

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Abstract. We propose a computational model for building a tactile body schema for a virtual human. The learned body structure of the agent can enable it to acquire a perception of the space surrounding its body, namely its peripersonal space. The model uses tactile and proprioceptive informations and relies on an algorithm which was originally applied with visual and proprioceptive sensor data. In order to feed the model, we present work on obtaining the nessessary sensory data only from touch sensors and the motor system. Based on this, we explain the learning process for a tactile body schema. As there is not only a technical motivation for devising such a model but also an application of peripersonal action space, an interaction example with a conversational agent is described.

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“Is It Within My Reach?” – An Agents Perspective

Cited by 5 publications

References 4 publications

Realism is not all! User engagement with task-related interface characters

Realism is not all! User engagement with task-related interface characters

A computational model of cooperative spatial behaviour for virtual humans*

Modeling Peripersonal Action Space for Virtual Humans Using Touch and Proprioception

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