The Presence of the Uncanny Valley Between Animation and Cinema

Author(s):  
Rodrigo Assaf ◽  
Sahra Kunz ◽  
Luís Teixeira

Despite all the technological advances in the field of computer graphics, the uncanny valley effect is still an observed phenomenon affecting not only how animated digital characters are developed but also the audience's reaction during a film session. With the emergence of computer-generated images being used in films, this chapter aims at presenting a multidisciplinary approach concerning the uncanny valley topic. This phenomenon is mainly explained by several psychological theories based on human perception; however, this chapter contributes to the discussion presenting a communication perspective based on the uses and gratification theory connected to the genre theory proposed by Daniel Chandler. In addition, the authors discuss how the technological evolution in rendering is helping out artists to cross the valley, which ends up being unveiled only by motion. As a result of this technical evolution, it is proposed a new animation art style category defined as quasi-real.

2021 ◽  
Author(s):  
Fumiya Yonemitsu ◽  
Kyoshiro Sasaki ◽  
Akihiko Gobara ◽  
Yuki Yamada

Technological advances in robotics have already produced robots that are indistinguishable from human beings. This technology is overcoming the uncanny valley, which refers to the unpleasant feelings that arise from humanoid robots that are similar in appearance to real humans to some extent. If humanoid robots with the same appearance are mass-produced and become commonplace, we may encounter circumstances in which people or human-like products have faces with the exact same appearance in the future. This leads to the following question: what impressions do clones elicit? To respond to this question, we examined what impressions images of people with the same face (clone images) induce. In the six studies we conducted, we consistently reported that clone images elicited higher eeriness than individuals with different faces; we named this new phenomenon the clone devaluation effect. We found that the clone devaluation effect reflected the perceived improbability of facial duplication. Moreover, this phenomenon was related to distinguishableness of each face, the duplication of identity, the background scene in observing clone faces, and avoidance reactions based on disgust sensitivity. These findings suggest that the clone devaluation effect is a product of multiple processes related to memory, emotion, and face recognition systems.


Perception ◽  
2017 ◽  
Vol 46 (12) ◽  
pp. 1386-1411 ◽  
Author(s):  
Shensheng Wang ◽  
Philippe Rochat

The uncanny valley hypothesis by Japanese roboticist Masahiro Mori posits a nonlinear relation between human replicas’ human likeness and the emotional responses they elicit. In three studies, we corroborated the uncanny valley hypothesis, using the uncanny phenomenon as a vehicle to shed a new light on human animacy perception. In Study 1, 62 participants rated emotional responses and human likeness of 89 artificial and human faces. In Study 2, another 62 participants conducted a visual looming task with the same 89 faces allowing for the measurement of perceived threat. Results support the uncanny valley hypothesis, suggesting that the uncanny feeling may serve a function to wary humans of the potential danger of entities crossing the animate–inanimate boundary. In Study 3, 36 participants sorted faces as either real or unreal as quickly as possible in a reaction time sorting task allowing for the measurement of categorical uncertainty associated with animacy perception. Faces associated with longer sorting reaction times were also those associated with the highest ratings of negative emotions, suggesting that categorical uncertainty in animacy detection is related to the uncanny feeling. Results are discussed in light of human animacy perception and new directions for future research are suggested.


2007 ◽  
Vol 16 (4) ◽  
pp. 337-351 ◽  
Author(s):  
Jun'ichiro Seyama ◽  
Ruth S. Nagayama

Roboticists believe that people will have an unpleasant impression of a humanoid robot that has an almost, but not perfectly, realistic human appearance. This is called the uncanny valley, and is not limited to robots, but is also applicable to any type of human-like object, such as dolls, masks, facial caricatures, avatars in virtual reality, and characters in computer graphics movies. The present study investigated the uncanny valley by measuring observers' impressions of facial images whose degree of realism was manipulated by morphing between artificial and real human faces. Facial images yielded the most unpleasant impressions when they were highly realistic, supporting the hypothesis of the uncanny valley. However, the uncanny valley was confirmed only when morphed faces had abnormal features such as bizarre eyes. These results suggest that to have an almost perfectly realistic human appearance is a necessary but not a sufficient condition for the uncanny valley. The uncanny valley emerges only when there is also an abnormal feature.


2020 ◽  
Author(s):  
Sujal Manohar

Face perception is an essential skill for human interaction and social learning, impacting how we build relationships and perceive the world around us. In the modern era, face processing remains important but confronts new challenges due to recent technological advances such as deepfake technology and AI-generated faces. These computer-generated (CG) faces may be difficult for our brains to distinguish from real faces, raising questions in the fields of criminal justice, politics, and animation, to name a few. This review explores the neurobiology of face processing and its interplay with affect, laying the foundation for an investigation into recent studies examining how humans differentiate between real and CG faces. Studies on the uncanny valley effect and pareidolia offer further insights as to how humans make this judgment and the possible boundaries of face perception. Additional research is needed to better understand this emerging area and possibly train human viewers to perform these judgments more accurately in the future.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254396
Author(s):  
Fumiya Yonemitsu ◽  
Kyoshiro Sasaki ◽  
Akihiko Gobara ◽  
Yuki Yamada

Technological advances in robotics have already produced robots that are indistinguishable from human beings. This technology is overcoming the uncanny valley, which refers to the unpleasant feelings that arise from humanoid robots that are similar in appearance to real humans to some extent. If humanoid robots with the same appearance are mass-produced and become commonplace, we may encounter circumstances in which people or human-like products have faces with the exact same appearance in the future. This leads to the following question: what impressions do clones elicit? To respond to this question, we examined what impressions images of people with the same face (clone images) induce. In the six studies we conducted, we consistently reported that clone images elicited higher eeriness than individuals with different faces; we named this new phenomenon the clone devaluation effect. We found that the clone devaluation effect reflected the perceived improbability of facial duplication. Moreover, this phenomenon was related to distinguishableness of each face, the duplication of identity, the background scene in observing clone faces, and avoidance reactions based on disgust sensitivity. These findings suggest that the clone devaluation effect is a product of multiple processes related to memory, emotion, and face recognition systems.


2020 ◽  
Author(s):  
Christopher Welker ◽  
David France ◽  
Alice Henty ◽  
Thalia Wheatley

Advances in artificial intelligence (AI) enable the creation of videos in which a person appears to say or do things they did not. The impact of these so-called “deepfakes” hinges on their perceived realness. Here we tested different versions of deepfake faces for Welcome to Chechnya, a documentary that used face swaps to protect the privacy of Chechen torture survivors who were persecuted because of their sexual orientation. AI face swaps that replace an entire face with another were perceived as more human-like and less unsettling compared to partial face swaps that left the survivors’ original eyes unaltered. The full-face swap was deemed the least unsettling even in comparison to the original (unaltered) face. When rendered in full, AI face swaps can appear human and avoid aversive responses in the viewer associated with the uncanny valley.


2014 ◽  
Author(s):  
Jessy Rose Goodman
Keyword(s):  

2019 ◽  
Vol 30 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Seo Young Kim ◽  
Bernd H. Schmitt ◽  
Nadia M. Thalmann
Keyword(s):  

2015 ◽  
Vol 24 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Himalaya Patel ◽  
Karl F. MacDorman

Just as physical appearance affects social influence in human communication, it may also affect the processing of advice conveyed through avatars, computer-animated characters, and other human-like interfaces. Although the most persuasive computer interfaces are often the most human-like, they have been predicted to incur the greatest risk of falling into the uncanny valley, the loss of empathy attributed to characters that appear eerily human. Previous studies compared interfaces on the left side of the uncanny valley, namely, those with low human likeness. To examine interfaces with higher human realism, a between-groups factorial experiment was conducted through the internet with 426 midwestern U.S. undergraduates. This experiment presented a hypothetical ethical dilemma followed by the advice of an authority figure. The authority was manipulated in three ways: depiction (digitally recorded or computer animated), motion quality (smooth or jerky), and advice (disclose or refrain from disclosing sensitive information). Of these, only the advice changed opinion about the ethical dilemma, even though the animated depiction was significantly eerier than the human depiction. These results indicate that compliance with an authority persists even when using an uncannily realistic computer-animated double.


Cognition ◽  
2014 ◽  
Vol 130 (3) ◽  
pp. 271-277 ◽  
Author(s):  
Lukasz Piwek ◽  
Lawrie S. McKay ◽  
Frank E. Pollick

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