Background The uncanny valley hypothesis states that users may experience discomfort when inter-acting with almost human-like artificial characters.Advancements in artificial intelligence,robotics,and computer graphic...Background The uncanny valley hypothesis states that users may experience discomfort when inter-acting with almost human-like artificial characters.Advancements in artificial intelligence,robotics,and computer graphics have led to the development of life-like virtual humans and humanoid robots.Revisiting this hypothesis is necessary to check whether they positively or negatively affect the current population,who are highly accustomed to the latest technologies.Methods In this study,we present a unique evaluation of the uncanny valley hypothesis by allowing participants to interact live with four humanoid robots that have varying levels of human-likeness.Each participant completed a survey questionnaire to evaluate the affinity of each robot.Additionally,we used deep learning methods to quantify the participants’emotional states using multimodal cues,including visual,audio,and text cues,by recording the participant-robot interactions.Results Multi-modal analysis and surveys provided interesting results and insights into the uncanny valley hypothesis.展开更多
Highly realistic virtual human models are rapidly becoming commonplace incomputer graphics. These models, often represented by complex shape and requiring labor-intensiveprocess, challenge the problem of automatic mod...Highly realistic virtual human models are rapidly becoming commonplace incomputer graphics. These models, often represented by complex shape and requiring labor-intensiveprocess, challenge the problem of automatic modeling. The problem and solutions to automaticmodeling of animatable virtual humans are studied. Methods for capturing the shape of real people,parameterization techniques for modeling static shape (the variety of human body shapes) and dynamicshape (how the body shape changes as it moves) of virtual humans are classified, summarized andcompared. Finally, methods for clothed virtual humans are reviewed.展开更多
基金Supported by the National Research Foundation,Singapore under its International Research Centers in Singapore Funding InitiativeInstitute for Media Innovation,Nanyang Technological University(IMI-NTU)。
文摘Background The uncanny valley hypothesis states that users may experience discomfort when inter-acting with almost human-like artificial characters.Advancements in artificial intelligence,robotics,and computer graphics have led to the development of life-like virtual humans and humanoid robots.Revisiting this hypothesis is necessary to check whether they positively or negatively affect the current population,who are highly accustomed to the latest technologies.Methods In this study,we present a unique evaluation of the uncanny valley hypothesis by allowing participants to interact live with four humanoid robots that have varying levels of human-likeness.Each participant completed a survey questionnaire to evaluate the affinity of each robot.Additionally,we used deep learning methods to quantify the participants’emotional states using multimodal cues,including visual,audio,and text cues,by recording the participant-robot interactions.Results Multi-modal analysis and surveys provided interesting results and insights into the uncanny valley hypothesis.
文摘Highly realistic virtual human models are rapidly becoming commonplace incomputer graphics. These models, often represented by complex shape and requiring labor-intensiveprocess, challenge the problem of automatic modeling. The problem and solutions to automaticmodeling of animatable virtual humans are studied. Methods for capturing the shape of real people,parameterization techniques for modeling static shape (the variety of human body shapes) and dynamicshape (how the body shape changes as it moves) of virtual humans are classified, summarized andcompared. Finally, methods for clothed virtual humans are reviewed.
