Navigation for digital actors based on synthetic vision, memory, and learning

Noser, Hansrudi; Renault, Olivier; Thalmann, Daniel; Thalmann, Nadia Magnenat

doi:10.1016/0097-8493(94)00117-h

Cited by 113 publications

(62 citation statements)

References 9 publications

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“…Fortunately, several works directly focussing on some aspects of spatial cognition for IVAs have emerged to increase believability of their spatial behaviour, including mapping, localisation, and navigation. Noser et al developed IVAs learning topological structure of the environment and navigating using this structure [15]. In a psychologically more plausible manner, Thomas and Donikian [23] addressed similar issue.…”

Section: Related Workmentioning

confidence: 99%

How Do Place and Objects Combine? “What-Where” Memory for Human-Like Agents

Brom

Korenko

Lukavský

2009

Intelligent Virtual Agents

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Abstract. Believable spatial behaviour is important for intelligent virtual agents acting in human-like environments, such as buildings or cities. Existing models of spatial cognition and memory for these agents are predominantly aimed at issues of navigation and learning of topology of the environment. The issue of representing information about possible objects' locations in a familiar environment, information that can evolve over long periods, has not been sufficiently studied. Here, we present a novel representation for "what-where" information: memory for locations of objects. On a simplified model of a virtual character living in a virtual house, we investigate how this representation is formed and how it evolves based on how objects are moved within the environment. The behaviour of the model is also compared with behaviour of real humans conducting an analogical task. The results allow us to conclude that this model can be incorporated to other memory models for virtual agents.

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Section: Related Workmentioning

confidence: 99%

How Do Place and Objects Combine? “What-Where” Memory for Human-Like Agents

Brom

Korenko

Lukavský

2009

Intelligent Virtual Agents

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“…This paper only discusses the visual perception of characters. Synthetic vision is an important method for visual perception [11], which can accurately simulate the vision from view of character. In this paper, each object is assigned a unique color code, to check which objects are visible to virtual character; the scene is rendered from the character's point of view with no texture (only with color by color ID for each object in Fig.2.…”

Section: Perception Of 3d Virtual Charactersmentioning

confidence: 99%

“…If an emotion is active, this module will create emotion expression, emotion expression code will be sent to behavior module. (11) The motion control module includes inverse kinematics arithmetic and motion captures arithmetic.…”

Section: Architecture Of 3d Virtual Charactersmentioning

confidence: 99%

An Emotion Model of 3D Virtual Characters in Intelligent Virtual Environment

Liu

Pan

2005

Lecture Notes in Computer Science

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Abstract. Human emotion is related to stimulus and cognitive appraisal. Emotion is very important to entertainment application of virtual reality. Emotion model of 3D virtual characters is a challenging branch of Intelligent Virtual Environment (IVE). A believable 3D character should be provided with emotion and perception. In general, a virtual character is regarded as an autonomous agent with sense, perception, behavior and action. An emotion model of 3D virtual characters on the basis of psychology theory is presented in this paper. Our work is to construct 3D virtual characters that have internal sensor and perception for external stimulus, and express emotion autonomously in real time. Firstly, architecture of a virtual character is set up by cognitive model; Secondly, emotion class is set up by OCC and Plutchik's emotion theory; Thirdly, some new concepts about emotion are presented with a general mathematical model which is relation among emotion, stimulus, motivation variable, personality variable. Fourthly, a perception model of 3D characters by Gibson's theory is introduced. As a result, an emotional animation demo system of 3D virtual character is implemented on PC.

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“…Noser et al presented a synthetic vision system that uses object-false coloring and dynamic octrees to represent the visual memory of the character who navigates combining global and local techniques [2].…”

Section: Introductionmentioning

confidence: 99%

Towards reactive navigation and attention skills for 3D intelligent characters

Lozano

Grimaldo

Villaplana

2003

Artificial Neural Nets Problem Solving Methods

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Abstract. This paper presents a neural design which is able to provide the necessary reactive navigation and attention skills for 3D embodied agents (virtual humanoids or characters). Based on Grossberg's neural model of conditioning [6], as recently implemented by Chang and Gaudiando [7], and according to the Adaptative Resonance Theory (ART) and the neuroscientific concepts associated, the neural design introduced has been divided in two main phases. Firstly, an environmentcategorization phase, where an on-line pattern recognition and categorization of the current agent sensory input data is carried out by a self organizing neural network, which will finally provide the agent's short term memory layer(STM). Secondly, and based on the classical conditioning paradigm, the model will associate the interesting STM states, from the navigation or attention points of view, to finally simulate these necessary skills for 3D characters or humanoids. Finally, we will show some experimental navigational results, through the integration of the model presented in 3D virtual environments.

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Navigation for digital actors based on synthetic vision, memory, and learning

Cited by 113 publications

References 9 publications

How Do Place and Objects Combine? “What-Where” Memory for Human-Like Agents

How Do Place and Objects Combine? “What-Where” Memory for Human-Like Agents

An Emotion Model of 3D Virtual Characters in Intelligent Virtual Environment

Towards reactive navigation and attention skills for 3D intelligent characters

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