Fitted avatars: automatic skeleton adjustment for self-avatars in virtual reality

In the era of the metaverse, self-avatars are gaining popularity, as they can enhance presence and provide embodiment when a user is immersed in Virtual Reality. They are also very important in collaborative Virtual Reality to improve communication through gestures. Whether we are using a complex motion capture solution or a few trackers with inverse kinematics (IK), it is essential to have a good match in size between the avatar and the user, as otherwise mismatches in self-avatar posture could be noticeable for the user. To achieve such a correct match in dimensions, a manual process is often required, with the need for a second person to take measurements of body limbs and introduce them into the system. This process can be time-consuming, and prone to errors. In this paper, we propose an automatic measuring method that simply requires the user to do a small set of exercises while wearing a Head-Mounted Display (HMD), two hand controllers, and three trackers. Our work provides an affordable and quick method to automatically extract user measurements and adjust the virtual humanoid skeleton to the exact dimensions. Our results show that our method can reduce the misalignment produced by the IK system when compared to other solutions that simply apply a uniform scaling to an avatar based on the height of the HMD, and make assumptions about the locations of joints with respect to the trackers.This work was funded by the Spanish Ministry of Science and Innovation (PID2021-122136OB-C21). Jose Luis Ponton was also funded by the Spanish Ministry of Universities (FPU21/01927).Peer ReviewedPostprint (published version

Sex differences in the association of postural control with indirect measures of body representations

Besides anthropometric variables, high-order body representations have been hypothesised to influence postural control. However, this has not been directly tested before. Moreover, some studies indicate that sex moderates the relationship of anthropometry and postural control. Therefore, as a proof of concept we investigated the association of body representations with postural control as well as the influence of participants’ sex/gender. Body image measures were assessed with a figural drawing task. Body schema was tested by a covert and an overt task. Body sway was measured during normal bipedal quiet standing with eyes closed (with/without neck extended). Statistical analysis consisted of hierarchical multiple linear regressions with the following regression steps: (1) sensory condition, (2) sex/gender, (3) age, (4) anthropometry, (5) body schema, (6) body image, (7) sex/gender-interactions. Across 36 subjects (19 females), body schema was significantly associated with body sway variability and open-loop control, in addition to commonly known influencing factors, such as sensory condition, gender, age and anthropometry. While in females, also body image dissatisfaction substantially was associated with postural control, this was not the case in males. Sex differences and possible causes why high-order body representations may influence concurrent sensorimotor control of body sway are discussed

How Does Variation in the Body Composition of Both Stimuli and Participant Modulate Self-Estimates of Men’s Body Size?

When measured in units of body mass index (BMI), how much variation in men’s self-estimates of body size is caused by i) variation in participants’ body composition and ii) variation in the apparent muscle mass and muscle tone of the stimuli being judged? To address this, we generated nine sets of male CGI bodies representing low, mid, and high muscle mass rendered at low, mid, and high muscle tone, from 18.75 to 40 BMI-hse units. BMI-hse units in this study are estimates of BMI derived from calibration equations predicting BMI from waist and hip circumference, age, sex, height, and ethnicity in the Health Survey for England databases. Forty-five healthy adult men estimated their body size using a yes-no paradigm for each combination of muscle mass/tone. We also measured participants’ body composition with Harpenden callipers and their body concerns with psychometric questionnaires. We show that stimulus variation in apparent muscle mass/tone can introduce differences up to ∼2.5 BMI-hse units in men’s self-estimates of body size. Moreover, men with the same actual BMI, but different body composition, showed up to ∼5-7 BMI-hse unit differences in self-estimates of body size. In the face of such large errors, we advocate that such judgments in men should be made instead by simultaneously manipulating both the adiposity and the muscle mass of stimuli which are appropriately calibrated for body composition, so that the participant can match the body size and shape they believe themselves to have to the stimulus they see

Visual Perception and Evaluation of Photo-Realistic Self-Avatars From 3D Body Scans in Males and Females

The creation or streaming of photo-realistic self-avatars is important for virtual reality applications that aim for perception and action to replicate real world experience. The appearance and recognition of a digital self-avatar may be especially important for applications related to telepresence, embodied virtual reality, or immersive games. We investigated gender differences in the use of visual cues (shape, texture) of a self-avatar for estimating body weight and evaluating avatar appearance. A full-body scanner was used to capture each participant's body geometry and color information and a set of 3D virtual avatars with realistic weight variations was created based on a statistical body model. Additionally, a second set of avatars was created with an average underlying body shape matched to each participant's height and weight. In four sets of psychophysical experiments, the influence of visual cues on the accuracy of body weight estimation and the sensitivity to weight changes was assessed by manipulating body shape (own, average) and texture (own photo-realistic, checkerboard). The avatars were presented on a large-screen display, and participants responded to whether the avatar's weight corresponded to their own weight. Participants also adjusted the avatar's weight to their desired weight and evaluated the avatar's appearance with regard to similarity to their own body, uncanniness, and their willingness to accept it as a digital representation of the self. The results of the psychophysical experiments revealed no gender difference in the accuracy of estimating body weight in avatars. However, males accepted a larger weight range of the avatars as corresponding to their own. In terms of the ideal body weight, females but not males desired a thinner body. With regard to the evaluation of avatar appearance, the questionnaire responses suggest that own photo-realistic texture was more important to males for higher similarity ratings, while own body shape seemed to be more important to females. These results argue for gender-specific considerations when creating self-avatars

Visual Perception and Evaluation of Photo-Realistic Self-Avatars From 3D Body Scans in Males and Females

The creation or streaming of photo-realistic self-avatars is important for virtual reality applications that aim for perception and action to replicate real world experience. The appearance and recognition of a digital self-avatar may be especially important for applications related to telepresence, embodied virtual reality, or immersive games. We investigated gender differences in the use of visual cues (shape, texture) of a self-avatar for estimating body weight and evaluating avatar appearance. A full-body scanner was used to capture each participant's body geometry and color information and a set of 3D virtual avatars with realistic weight variations was created based on a statistical body model. Additionally, a second set of avatars was created with an average underlying body shape matched to each participant's height and weight. In four sets of psychophysical experiments, the influence of visual cues on the accuracy of body weight estimation and the sensitivity to weight changes was assessed by manipulating body shape (own, average) and texture (own photo-realistic, checkerboard). The avatars were presented on a large-screen display, and participants responded to whether the avatar's weight corresponded to their own weight. Participants also adjusted the avatar's weight to their desired weight and evaluated the avatar's appearance with regard to similarity to their own body, uncanniness, and their willingness to accept it as a digital representation of the self. The results of the psychophysical experiments revealed no gender difference in the accuracy of estimating body weight in avatars. However, males accepted a larger weight range of the avatars as corresponding to their own. In terms of the ideal body weight, females but not males desired a thinner body. With regard to the evaluation of avatar appearance, the questionnaire responses suggest that own photo-realistic texture was more important to males for higher similarity ratings, while own body shape seemed to be more important to females. These results argue for gender-specific considerations when creating self-avatars

Distributed Implementation of eXtended Reality Technologies over 5G Networks

Mención Internacional en el título de doctorThe revolution of Extended Reality (XR) has already started and is rapidly expanding as technology advances. Announcements such as Meta’s Metaverse have boosted the general interest in XR technologies, producing novel use cases. With the advent of the fifth generation of cellular networks (5G), XR technologies are expected to improve significantly by offloading heavy computational processes from the XR Head Mounted Display (HMD) to an edge server. XR offloading can rapidly boost XR technologies by considerably reducing the burden on the XR hardware, while improving the overall user experience by enabling smoother graphics and more realistic interactions. Overall, the combination of XR and 5G has the potential to revolutionize the way we interact with technology and experience the world around us. However, XR offloading is a complex task that requires state-of-the-art tools and solutions, as well as an advanced wireless network that can meet the demanding throughput, latency, and reliability requirements of XR. The definition of these requirements strongly depends on the use case and particular XR offloading implementations. Therefore, it is crucial to perform a thorough Key Performance Indicators (KPIs) analysis to ensure a successful design of any XR offloading solution. Additionally, distributed XR implementations can be intrincated systems with multiple processes running on different devices or virtual instances. All these agents must be well-handled and synchronized to achieve XR real-time requirements and ensure the expected user experience, guaranteeing a low processing overhead. XR offloading requires a carefully designed architecture which complies with the required KPIs while efficiently synchronizing and handling multiple heterogeneous devices. Offloading XR has become an essential use case for 5G and beyond 5G technologies. However, testing distributed XR implementations requires access to advanced 5G deployments that are often unavailable to most XR application developers. Conversely, the development of 5G technologies requires constant feedback from potential applications and use cases. Unfortunately, most 5G providers, engineers, or researchers lack access to cutting-edge XR hardware or applications, which can hinder the fast implementation and improvement of 5G’s most advanced features. Both technology fields require ongoing input and continuous development from each other to fully realize their potential. As a result, XR and 5G researchers and developers must have access to the necessary tools and knowledge to ensure the rapid and satisfactory development of both technology fields. In this thesis, we focus on these challenges providing knowledge, tools and solutiond towards the implementation of advanced offloading technologies, opening the door to more immersive, comfortable and accessible XR technologies. Our contributions to the field of XR offloading include a detailed study and description of the necessary network throughput and latency KPIs for XR offloading, an architecture for low latency XR offloading and our full end to end XR offloading implementation ready for a commercial XR HMD. Besides, we also present a set of tools which can facilitate the joint development of 5G networks and XR offloading technologies: our 5G RAN real-time emulator and a multi-scenario XR IP traffic dataset. Firstly, in this thesis, we thoroughly examine and explain the KPIs that are required to achieve the expected Quality of Experience (QoE) and enhanced immersiveness in XR offloading solutions. Our analysis focuses on individual XR algorithms, rather than potential use cases. Additionally, we provide an initial description of feasible 5G deployments that could fulfill some of the proposed KPIs for different offloading scenarios. We also present our low latency muti-modal XR offloading architecture, which has already been tested on a commercial XR device and advanced 5G deployments, such as millimeter-wave (mmW) technologies. Besides, we describe our full endto- end complex XR offloading system which relies on our offloading architecture to provide low latency communication between a commercial XR device and a server running a Machine Learning (ML) algorithm. To the best of our knowledge, this is one of the first successful XR offloading implementations for complex ML algorithms in a commercial device. With the goal of providing XR developers and researchers access to complex 5G deployments and accelerating the development of future XR technologies, we present FikoRE, our 5G RAN real-time emulator. FikoRE has been specifically designed not only to model the network with sufficient accuracy but also to support the emulation of a massive number of users and actual IP throughput. As FikoRE can handle actual IP traffic above 1 Gbps, it can directly be used to test distributed XR solutions. As we describe in the thesis, its emulation capabilities make FikoRE a potential candidate to become a reference testbed for distributed XR developers and researchers. Finally, we used our XR offloading tools to generate an XR IP traffic dataset which can accelerate the development of 5G technologies by providing a straightforward manner for testing novel 5G solutions using realistic XR data. This dataset is generated for two relevant XR offloading scenarios: split rendering, in which the rendering step is moved to an edge server, and heavy ML algorithm offloading. Besides, we derive the corresponding IP traffic models from the captured data, which can be used to generate realistic XR IP traffic. We also present the validation experiments performed on the derived models and their results.This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Narciso García Santos.- Secretario: Fernando Díaz de María.- Vocal: Aryan Kaushi