Kenny Mitchell

DanceGraph is an architecture for synchronized online dancing overcoming the latency of networked body pose sharing. We break down this challenge by developing a real-time bandwidth-efficient architecture to minimize lag and reduce the timeframe of required motion prediction for synchronization with the music's rhythm. In addition, we show an interactive method for the parameterized stylization of dance motions for rhythmic dance using online dance correctives.

HoloJig offers an interactive, speech-to-VR, virtual reality experience that generates diverse environments in real-time based on live spoken descriptions. Unlike traditional VR systems that rely on pre-built assets, HoloJig dynamically creates personalized and immersive virtual spaces with depth-based parallax 3D rendering, allowing users to define the characteristics of their immersive environment through verbal prompts. This generative approach opens up new possibilities for interactive experiences, including simulations, training, collaborative workspaces, and entertainment. In addition to speech-to-VR environment generation, a key innovation of HoloJig is its progressive visual transition mechanism, which smoothly dissolves between previously generated and newly requested environments, mitigating the delay caused by neural computations. This feature ensures a seamless and continuous user experience, even as new scenes are being rendered on remote servers.

We present a classroom enhanced with augmented reality video display in which students adopt snapshots of their corresponding virtual personas according to their teacher’s live articulated spoken educational theme, linearly, such as historical figures, famous scientists, cultural icons, and laterally according to archetypal categories such as world dance styles. We define a structure of generative AI prompt guidance to assist teachers with focused specified visual role embodiment stylization. By leveraging role-based immersive embodiment, our proposed approach enriches pedagogical practices that prioritize experiential learning.

Audio plays a key role in the sense of immersion and presence in VR, as it correlates to improved enjoyment of content. We share results of a perception study on the ability of listeners to recognise auditory occlusion due to the presence of a human being in the direct sound path. We ran two-alternative forced choice trials to test for effects of occluder body type and distance from sound source on recognition of auditory occlusion. Results show that audio cues allow listeners to significantly detect the presence or absence of an occluder, and that position of the occluder relative to the listener and sound source, as well as occluder body type modulate detection rates. Synthesised audio achieved, in selected conditions, better occlusion detection than recorded audio. The work provides details on what filtering occurs across 26 1/3 octave frequency bands when a person comes between a listener and a sound source. This research will inform the recreation of auditory effects in virtual shared spaces aimed at music and dancing, due to the presence of other avatars.

Stylized avatars are common virtual representations used in VR to support interaction and communication between remote collaborators. However, explicit expressions are notoriously difficult to create, mainly because most current methods rely on geometric markers and features modeled for human faces, not stylized avatar faces. To cope with the challenge of emotional and expressive generating talking avatars, we build the Emotional Talking Avatar Dataset which is a talking-face video corpus featuring 6 different stylized characters talking with 7 different emotions. Together with the dataset, we also release an emotional talking avatar generation method which enables the manipulation of emotion. We validated the effectiveness of our dataset and our method in generating audio based puppetry examples, including comparisons to state-of-the-art techniques and a user study. Finally, various applications of this method are discussed in the context of animating avatars in VR.

Our aim is to improve animation production techniques' efficiency and effectiveness. We present two real-time solutions which drive character expressions in a geometrically consistent and perceptually valid way. Our first solution combines keyframe animation techniques with machine learning models. We propose a 3D emotion transfer network makes use of a 2D human image to generate a stylized 3D rig parameter. Our second solution combines blendshape-based motion capture animation techniques with machine learning models. We propose a blendshape adaption network which generates the character rig parameter motions with geometric consistency and temporally stability. We demonstrate the effectiveness of our system by comparing it to a commercial product Faceware. Results reveal that ratings of the recognition, intensity, and attractiveness of expressions depicted for animated characters via our systems are statistically higher than Faceware. Our results may be implemented into the animation pipeline, supporting animators to create expressions more rapidly and precisely.

We introduce live character conversational interactions in Intermediated Reality to bring real-world objects to life in Augmented Reality (AR) and Artificial Intelligence (AI). The AI recognizes live speech and generates short character responses, syncing the character’s facial expressions with speech audio. The Intermediated Reality AR warping technique allows for a high degree of realism in the animated facial expressions and movements reusing live video optical appearance direct from the device’s embedded camera. The proposed applications of Intermediated Reality with AI are exemplified through the captivating fusion of these technologies in toy interactive storytelling broadcasts and social telepresence scenarios. This innovative combination allows individuals to engage with AI characters in a natural and intuitive manner, creating new opportunities for social engagement and entertainment.

GAMES creatively take place in imaginative worlds informed by, but often not limited by, real-world challenges, and this advantageously provides an accelerated environment for innovation, where concepts and ideas can be explored unencumbered by physical or conventional restrictions. This editorial considers the role of artificial intelligence (AI) in GAMES in the context of emerging systems seemingly beginning to exhibit artificial general intelligence (AGI) and where there is much fertile ground to be found in synthetic constrained worlds to explore, understand, and prepare for its increasing presence in our lives.