When simulating large crowds, it is inevitable that the models and motions of many virtual characters will be cloned. However, the perceptual impact of this trade-off has never been studied. In this paper, we consider the ways in which an impression of variety can be created and the perceptual consequences of certain design choices. In a series of experiments designed to test people's perception of variety in crowds, we found that clones of appearance are far easier to detect than motion clones. Furthermore, we established that cloned models can be masked by color variation, random orientation, and motion. Conversely, the perception of cloned motions remains unaffected by the model on which they are displayed. Other factors that influence the ability to detect clones were examined, such as proximity, model type and characteristic motion. Our results provide novel insights and useful thresholds that will assist in creating more realistic, heterogeneous crowds.
No abstract
For real-time animation of characters, Level of Detail (LOD) techniques are usually deployed to achieve optimal efficiency and realism. Tools that can aid an application designer or developer to deploy simplification methods and LOD representations under different circumstances are therefore needed. In this paper we explore the perception of texture, silhouette and lighting artifacts on simplified character models, including the effect animation intensity has on the perceptibility of these artifacts. We propose novel methods to simulate each artifact separately, and test their effects in isolation and cumulatively. Our results provide useful insights and guidelines, including the importance of silhouette preservation. An adaptation of PerceptualDiff for predicting simplification detection has been developed, which can be used to guide automatic model placement and LOD selection in realtime character applications.
Figure 1: Variety types tested in the Selective Variation Experiment: (1) original character, (2) top texture variation, (3) face geometry variation, (4) face texture variation, (5 -9) head accessories. AbstractPopulated virtual environments need to be simulated with as much variety as possible. By identifying the most salient parts of the scene and characters, available resources can be concentrated where they are needed most. In this paper, we investigate which body parts of virtual characters are most looked at in scenes containing duplicate characters or clones. Using an eye-tracking device, we recorded fixations on body parts while participants were asked to indicate whether clones were present or not. We found that the head and upper torso attract the majority of first fixations in a scene and are attended to most. This is true regardless of the orientation, presence or absence of motion, sex, age, size, and clothing style of the character. We developed a selective variation method to exploit this knowledge and perceptually validated our method. We found that selective colour variation is as effective at generating the illusion of variety as full colour variation. We then evaluated the effectiveness of four variation methods that varied only salient parts of the characters. We found that head accessories, top texture and face texture variation are all equally effective at creating variety, whereas facial geometry alterations are less so. Performance implications and guidelines are presented.
Populated virtual environments need to be simulated with as much variety as possible. By identifying the most salient parts of the scene and characters, available resources can be concentrated where they are needed most. In this paper, we investigate which body parts of virtual characters are most looked at in scenes containing duplicate characters or clones. Using an eye-tracking device, we recorded fixations on body parts while participants were asked to indicate whether clones were present or not. We found that the head and upper torso attract the majority of first fixations in a scene and are attended to most. This is true regardless of the orientation, presence or absence of motion, sex, age, size, and clothing style of the character. We developed a selective variation method to exploit this knowledge and perceptually validated our method. We found that selective colour variation is as effective at generating the illusion of variety as full colour variation. We then evaluated the effectiveness of four variation methods that varied only salient parts of the characters. We found that head accessories, top texture and face texture variation are all equally effective at creating variety, whereas facial geometry alterations are less so. Performance implications and guidelines are presented.
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