Recent advances in parallel processing have boosted computing power, enabling complex graphics rendering and fast convergence of neural network-based algorithms. Complex graphical User Interfaces in the form of 3D Virtual Humans (3DVH) with high-fidelity may be developed faster and connected with user feedback for interactive behavior (1).
3DVH can be categorized on many dimensions based on their interactivity or lack of it, based on their emotional expressiveness and level of autonomy as follows:
These are virtual characters that do not move or interact with users. They are often used in video games or animated films.
These are virtual characters that move and have some level of interactivity, but they do not respond to user input. They are often used in Virtual Reality experiences or in customer service applications.
These are virtual characters that can interact with users in real time using natural language processing and machine learning. They can respond to user input and carry out complex tasks. They are often used in customer service, training, and other applications where human-like interactions are required.
These are virtual characters that can display emotions and can adjust their behavior accordingly. They can be used in virtual therapy, customer service, and other applications where emotional intelligence is a key factor.
These are virtual characters that can make decisions, take actions, and adapt to the environment without human intervention. They are capable of learning and evolving over time. Such software systems are still in the Research and Development stage (R&D).
One of the key components of 3D virtual human assistants’ development is the way in which they convey emotion and recognize it upon interaction with the user. Computer vision techniques may be used for human emotion recognition from facial expressions; however, emotion can also be detected through a combination of biosensor signal analysis (2). Automatic emotion recognition methods can be divided into the following categories:
The method(s) used will be determined by the specific application as well as the desired level of accuracy and complexity. Multiple methods may be used in conjunction in some cases to provide a more accurate and reliable assessment of a person's emotions. Combining high-fidelity computer graphics (CG) and machine learning techniques is the next step in 3DVH interface development. A recent study found that participants experienced lower levels of negative emotional states after sharing personal emotional events and interacting with 3DVH tasked with delivering emotional or cognitive support (3). Providing emotional and cognitive support to a patient while adjusting to real-time changes in their emotional state and expressions can yield better treatment outcomes.
Natural language processing (NLP) is used by virtual humans to understand and respond to spoken and written language, enabling more human-like interactions.
Virtual humans use computer vision to analyze and respond to nonverbal cues such as gestures and facial expressions, which improves interaction realism.
On large datasets, virtual humans can be trained to make more informed decisions and provide better responses.
3D virtual humans are made more engaging for users by using interactive animation techniques to create lifelike movements and expressions.
3D virtual humans can interact with users more naturally by using multiple input modalities such as speech, gestures, and touch.
While emotional intelligence is still a challenge, these advancements in technology have enabled 3D virtual humans to become more intelligent, realistic, and human-like, making them useful to an even wider range of applications in the near future.
(1) Unreal’s Metahuman Creator software, last accessed on 02.07.2023.
(2) Adyapady, R. R., and B. Annappa. 2023. "A comprehensive review of facial expression recognition techniques." Multimedia Systems 29: 73–103.
(3) Lisanne S. Pauw, Disa A. Sauter, Gerben A. van Kleef, Gale M. Lucas, Jonathan Gratch, and Agneta H. Fischer, 2022. "The avatar will see you now: Support from a virtual human provides socio-emotional benefits." Computers in Human Behavior 136.
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