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The '''Virtual Human Interaction Lab''' ('''VHIL''') at [[Stanford University]] was founded in 2003 by Professor Jeremy Bailenson, associate professor of communication at Stanford University. The lab conducts research for the Communication Department.
==History==
==Faculty and research staff==
*'''Coral Compass: Fighting Climate Change in Palau''' (2018) - world premiere at the Tribeca Film Festival in 2018. In this 360 experience, viewers travel to Palau. The piece focuses on how the leaders of Palau is working with scientists to adapt to climate change.<ref>http://vhil.stanford.edu/coralcompass/</ref>
==Research==
==Current research==
===DigitalCurrent anonymity===
The*Digital anonymity - in 2010, the group iswas studying how digital media users who anonymize themselves via their avatars may be perceived differently from media users who use avatars that resemble their physical world selves. <ref name="Avatar">[http://news.stanford.edu/news/2010/february22/avatar-behavior-study-022510.html/ Avatar Behavior Study]</ref>▼
▲The group is studying how digital media users who anonymize themselves via their avatars may be perceived differently from media users who use avatars that resemble their physical world selves.
===Mediators and mimicry===
A mediator's success hinges on two important factors: impartiality and rapport. Ironically, the process of establishing rapport can undermine the mediator's ability to convey a sense of impartiality. Thus, mediators face a dilemma – a dilemma that we believe [[digital media]] might be able to help solve. We are how exploring the affordances of [[online dispute resolution]] (ODR) may help mediators strike a delicate balance between developing rapport and maintaining impartiality. One area that is of particular interest to us is digital mimicry. Mimicry is known to elicit a wide variety of favorable responses; using tracking technology and computer algorithms we can make virtual mediators subtly yet perfectly mimic disputants' head movements.
===Out-of-body experience===
What if the virtual self could "feel" in a virtual world the same way the physical self can feel in the physical world? Navigating virtual 3D environments, performing remote surgery, and tanning on a virtual island would become second-nature at this level of full immersion. We are studying ways to create and measure this phenomenon, known as self-presence, or an out-of-body experience. Current questions we are asking in this research area include what stimuli are necessary to induce digital body ownership and what modifications of avatars and virtual environments increase self-presence.
===Augmented perspective taking===
*Mediators and mimicry - researching how [[online dispute resolution]] (ODR) may help mediators strike a delicate balance between developing rapport and maintaining impartiality.
Perspective taking is the ability to mentally put oneself in the shoes of another to imagine what the other person might be thinking and feeling in a certain situation. Immersive virtual environments allow people to vividly share the perceptual experiences of others as if they are in the heat of the moment. In essence, our abilities to take the perspective of another person can be augmented by viscerally sharing their experiences - seeing, hearing, and feeling what the other person did in a particular situation. We can now literally climb into the skin of the other person to fully embody their body and senses. Current projects explore how novel affordances of interactive digital media such as immersion and interactivity can enhance the ability to understand other minds and how the virtual experience can influence our attitudes and behaviors.
*Out-of-body experience - studies self-presence, or an out-of-body experience.
===Self-endorsing===
*Augmented perspective taking - researching how immersion and interactivity can enhance the ability to understand other minds and how the virtual experience can influence our attitudes and behaviors.
Self-endorsing is a novel persuasion strategy made possible by the advancement of interactive digital media. The self is no longer just a passive receiver of information, but can simultaneously partake in the formation and dispersion of persuasive messages, persuading the self with the self. What may have sounded like a topic of a futuristic science fiction movie can now be easily and rapidly done using simple graphics software. Tapping into the framework of self-referencing, research on self-endorsing explores how using the self as the source of persuasive messages can powerfully influence attitudes and behaviors in various persuasive contexts.
*Self-endorsing - researches how using the self as the source of persuasive messages can influence attitudes and behaviors in various persuasive contexts.
===Automatic facial feature detection and analyses===
*Automatic facial feature detection and analyses - this methodology uses just a small webcam and computer software to predict an individual's errors and performance quality based only on facial features that are tracked and logged automatically.
While most prior research on facial expressions involve some form of manual coding by human coders based on established facial coding systems (e.g., FACS), this methodology uses just a small webcam and computer software to predict an individual's errors and performance quality based only on facial features that are tracked and logged automatically. Using just the first five to seven minutes of facial feature data, researchers were able to predict a participant's performance on a 30-minute experimental task with up to 90% accuracy. There are countless applications for this methodology that would facilitate research of other media effects. For instance, this methodology can predict purchasing decisions based on facial expressions (e.g., "buying" face vs. "not-buying" face) while participants engage in an online shopping task. Researchers can also monitor emotional fluctuations in real time as people make their selection of media content and verify whether or not the choices are contributing toward maintaining a good mood (i.e., mood management theory; Zillmann) based on their facial expressions. In addition, advertisers could benefit by receiving real-time data on the participant's responses to advertisements. Automatic facial feature analysis is not yet a perfect 'looking glass' to a person's mind, but its advantages are obvious and promising.
==Past=Former researchtopics==
The lab has studied topics such as:
*[[Proteus effect]]
*[[Transformed social interaction]]
*Facial Identity Capture<ref>[http://vhil.stanford.edu/pubs/2005/identity-capture.html/ Identity Capture]</ref> and Presidential Candidate Preference - it was found that by morphing a subject's face in a 40:60 ratio with that of John Kerry and George W. Bush, the subject was more likely to prefer the candidate that shared their features. This study has implications concerning the use of a voter's image and overall face morphing during national elections to sway a voter's decision.
* Virtual aging's affect on financial decisions<ref name="Abc">[http://abcnews.go.com/Technology/virtual-reality-study-encourages-subjects-save-future/story?id=12358259/ Virtual Reality Encourages Subject to Save for the Future] </ref>▼*Virtual aging's affect on financial decisions
*Eye witness testimony and virtual police lineups - In collaboration with the [[Research Center for Virtual Environments and Behavior]], the [[National Science Foundation]], and the [[Federal Judicial Center]], VHIL examined the capabilities of pointing out witnesses during a police lineup while in a virtual environment.
*Diversity simulation - allowing participants to experience another race or gender
== External links ==
*[http://www.stanfordvr.com/ Virtual Human Interaction Lab]
*[http://news.stanford.edu/news/2010/february22/avatar-behavior-study-022510.html/ Avatar Behavior Study]
▲*[http://abcnews.go.com/Technology/virtual-reality-study-encourages-subjects-save-future/story?id=12358259/ Virtual Reality Encourages Subject to Save for the Future]
*[http://vhil.stanford.edu/pubs/2005/identity-capture.html/ Identity Capture]
[[Category:Stanford University]]
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