Sven Seele

Modeling Sensation for an Intelligent Virtual Agent’s Perception Process

Perception is an important aspect of cognition since it forms the basis for further decision-making processes. In this contribution, the overall architecture of our synthetic perception for agents framework (SynPeA) for simulating a virtual entities perception is presented. We discuss aspects of modeling visual sensation and propose mechanisms for virtual sensors and memory. Different visual sensing approaches are compared by applying them to an artificial evaluation scenario. The evaluations show promising results with respect to performance and quality.

Adaptive Decision Making in Microsimulations of Urban Traffic in Virtual Environments

To improve the plausibility of driving and interaction as well as the perceived realism of agents in interactive media, we extend cognitive traffic agents based on personality profiles with emotions. As proof of concept a scenario with a narrowing road was evaluated. To enable agents to handle these scenarios, an existing lane change model was adapted to model the required decision processes and incorporate the driving style defined by static and dynamic aspects of the agents.

Integrating stereoscopic video in 3d games

Recent advances in commercial technology increase the use of stereoscopy in games. While current applications display existing games in real-time rendered stereoscopic 3D, future games will also feature S3D video as part of the virtual game world, in interactive S3D movies, or for new interaction methods. Compared to the rendering of 2D video within a 3D game scene, displaying S3D video includes some technical challenges related to rendering and adaption of the depth range. Rendering is exclusively possible on professional hardware not appropriate for gaming. Our approach, Multi-pass Stereoscopic Video Rendering (MSVR), allows to present stereoscopic video streams within game engines on consumer graphics boards. We further discuss aspects of performance and occlusion of virtual objects. This allows developers and other researchers to easily apply S3D video with current game engines to explore new innovations in S3D gaming.

Efficient Mesoscopic Simulations for Persistent Agents in 3D-Applications and Games

To save computational resources, traffic simulations in virtual environments and digital games often remove entities from the simulation once they leave the users visual field of view. This can lead to inconsistencies within the simulated world and break the immersive effect. To counter this effect, we propose a system consisting of a regular microscopic simulation around the user and an additional less detailed simulation layer beyond the users immediate surroundings. The new layer performs a mesoscopic simulation based on the FastLane model, utilizing elements from queuing theory. With this hybrid approach it is possible to simulate a reasonable amount of detailed traffic participants as well as a much larger number of less detailed, but persistent traffic participants. As a result it is possible to simulate entities with complex behavior close to the user while maintaining reasonable traffic densities throughout the entire system.

Dynamic Emotional States based on Personality Profiles for Adaptive Agent Behavior Patterns

Realism and plausibility of computer controlled entities in entertainment software have been enhanced by adding both static personalities and dynamic emotions. Here a generic model is introduced which allows the transfer of findings from real-life personality studies to a computational model. This information is used for decision making. The introduction of dynamic event-based emotions enables adaptive behavior patterns. The advantages of this new model have been validated with a four-way crossroad in a traffic simulation. Driving agents using the introduced model enhanced by dynamics were compared to agents based on static personality profiles and simple rule-based behavior. It has been shown that adding an adaptive dynamic factor to agents improves perceivable plausibility and realism. It also supports coping with extreme situations in a fair and understandable way.

YouDash3D: exploring stereoscopic 3D gaming for 3D movie theaters

Along with the success of the digitally revived stereoscopic cinema, events beyond 3D movies become attractive for movie theater operators, i.e. interactive 3D games. In this paper, we present a case that explores possible challenges and solutions for interactive 3D games to be played by a movie theater audience. We analyze the setting and showcase current issues related to lighting and interaction. Our second focus is to provide gameplay mechanics that make special use of stereoscopy, especially depth-based game design. Based on these results, we present YouDash3D, a game prototype that explores public stereoscopic gameplay in a reduced kiosk setup. It features live 3D HD video stream of a professional stereo camera rig rendered in a real-time game scene. We use the effect to place the stereoscopic effigies of players into the digital game. The game showcases how stereoscopic vision can provide for a novel depth-based game mechanic. Projected trigger zones and distributed clusters of the audience video allow for easy adaptation to larger audiences and 3D movie theater gaming.

A Semantic Road Network Model for traffic simulations in virtual environments: Generation and integration

Typically, virtual traffic networks are enhanced by semantic information to simplify certain processes in traffic simulations such as navigation or decision making. In this paper, we introduce an extendable model representing road network logics (RNL) which allows the integration of such semantic information. For our specific application, we focused on the following elements: road geometry, paths leading through junctions, right of way priorities and road features. Furthermore, we describe our traffic simulation approach, which contains two layers of complexity, and show how these two layers are combined within the RNL. Since the manual setup of such RNL is time-consuming and error prone, an approach for automatically generating RNL based on standardized OpenDRIVE data is introduced. For evaluation purposes, generated RNL were integrated into 3D scenes. The mapping of the RNL to the environment was examined and simulations were run for empirical validation. As a result, the automatically generated RNL could be successfully matched with the created 3D scenes, allowing our traffic simulation approach to be run on the final scenes. Additionally, a comparison between generation times of the RNL and estimates of the time required to manually create RNL showed significant time savings, in one case of more than 300 hours.

Integration of Multi-modal Cues in Synthetic Attention Processes to Drive Virtual Agent Behavior

Simulations and serious games require realistic behavior of multiple intelligent agents in real-time. One particular issue is how attention and multi-modal sensory memory can be modeled in a natural but effective way, such that agents controllably react to salient objects or are distracted by other multi-modal cues from their current intention. We propose a conceptual framework that provides a solution with adherence to three main design goals: natural behavior, real-time performance, and controllability. As a proof of concept, we implement three major components and showcase effectiveness in a real-time game engine scenario. Within the exemplified scenario, a visual sensor is combined with static saliency probes and auditory cues. The attention model weighs bottom-up attention against intention-related top-down processing, controllable by a designer using memory and attention inhibitor parameters. We demonstrate our case and discuss future extensions.

Here's Looking At You Anyway!: How Important is Realistic Gaze Behavior in Co-located Social Virtual Reality Games?

Simulating eye movements for virtual humans or avatars can improve social experiences in virtual reality (VR) games, especially when wearing head mounted displays. While other researchers have already demonstrated the importance of simulating meaningful eye movements, we compare three gaze models with different levels of fidelity regarding realism: (1) a base model with static fixation and saccadic movements, (2) a proposed simulation model that extends the saccadic model with gaze shifts based on a neural network, and (3) a users real eye movements recorded by a proprietary eye tracker. Our between-groups design study with 42 subjects evaluates impact of eye movements on social VR user experience regarding perceived quality of communication and presence. The tasks include free conversation and two guessing games in a co-located setting. Results indicate that a high quality of communication in co-located VR can be achieved without using extended gaze behavior models besides saccadic simulation. Users might have to gain more experience with VR technology before being able to notice subtle details in gaze animation. In the future, remote VR collaboration involving different tasks requires further investigation.

Comparison of Two Inventory Design Concepts in a Collaborative Virtual Reality Serious Game

Inventory design in games is crucial when it comes to managing in-game items efficiently. In multi-user settings, an additional goal is to support awareness concerning a co-players inventory and his/her available actions. Especially in virtual reality (VR), presence and immersion are vital aspects of the experience, suggesting real-world metaphors for interface design. The presented work examines two basic inventory paradigms: an abstract menu-based inventory and a metaphoric virtual belt. Both systems are implemented in a serious game prototype for paramedic training in VR, then evaluated in a between-group design study with paramedic trainees inexperienced in VR technology. While both solutions offer comparable usability and presence scores, the results suggest future optimization.