Correlation between Actual versus Perceived Body Mass Index using a 3D Avatar on Female Football and Rugby Athletes

Introduction: The pressures of body image can be considered as demoralising, especially within the female sporting environment, where female athletes often express the greatest number of negative thoughts and feelings towards their own body shape, appearance, and dissatisfaction. Research surrounding body image, body composition and body mass index (BMI) has shown that when participants use visual impressions, for perceived body image (PBI) they have failed to produce realistic images and often lacked body stimuli with realistic weight manipulations (Madrigal, 2000). To portray more realistic statistically probable weight manipulations of a personalised stimuli, a 3D Avatar can be used to establish how female athletes perceive their body image. Therefore, the main objective of this investigation is to determine the correlation between actual and perceived BMI using a 3D Avatar within female athletes. Method:n =18 female participants between the ages of 18–23 years of age and competing in football and rugby at club and university level were recruited. Stretched stature (m) and body mass (kg) were taken and values used to calculate actual (kg/m²) and perceived BMI. A computer generated (Unity Player) 3D Avatar, with a visual slide from an underweight to average to obese continuum, was used to assess participants perceived BMI. P value was set at < 0.05 and a Paired Student t-Test was used to test for the difference. A Pearson’s Correlation Coefficient was then used to test the strength of the correlation between the actual and perceived BMI. Results: Actual BMI ranged from 19.5 - 36.9 (x̄ 25.1 ± 4.7), whereas the perceived BMI ranged from 23.2 - 30.8 (x̄ 26.7 ± 2.6). A Paired Student t–test set at P < 0.05 suggested a significant difference between actual and perceived BMI (P = 0.023), and a Pearson’s Correlation Coefficient test confirmed a strong correlation of r = 0.875. Conclusion: Results indicated that perceived BMI was higher than the participants actual BMI and suggested that female athletes competing in football and rugby have a large amount of body dissatisfaction.

3D Avatar Approach for Continuous Sign Movement Using Speech/Text

Sign language is a visual language for communication used by hearing-impaired people with the help of hand and finger movements. Indian Sign Language (ISL) is a well-developed and standard way of communication for hearing-impaired people living in India. However, other people who use spoken language always face difficulty while communicating with a hearing-impaired person due to lack of sign language knowledge. In this study, we have developed a 3D avatar-based sign language learning system that converts the input speech/text into corresponding sign movements for ISL. The system consists of three modules. Initially, the input speech is converted into an English sentence. Then, that English sentence is converted into the corresponding ISL sentence using the Natural Language Processing (NLP) technique. Finally, the motion of the 3D avatar is defined based on the ISL sentence. The translation module achieves a 10.50 SER (Sign Error Rate) score.

Development of arabic sign language dictionary using 3D avatar technologies

<span>The arabic sign language (ArSL) is the natural language of the deaf community in Arabic countries. ArSL suffers from a lack of resources such as unified dictionaries and corpora. In this work, a dictionary of Arabic language to ArSL has been constructed as a part of a translation system. The Arabic words are converted into hamburg notation system (HamNoSys) using eSign editor Software. HamNoSys was used to create manual parameters (handshape, hand orientation, hand location, and hand movement), while non-manual parameters (facial expressions, shoulder raising, mouthing gesture, head tilting, and body movement) added by using (mouth, face, and limbs) in the eSign editor software. The sign then converted to the sign gesture markup language (SiGML) file, and later 3D avatar interprets the SiGML file scripts to the animated sign. The constructed dictionary has three thousand signs; therefore, it can be adopted for the translation system in which written text can be transformed into sign language and can be utilized for the education of deaf people. The dictionary will be available as a free resource for researchers. It is hard and time-consuming work, but it is an essential step in machine translation of whole Arabic text to ArSL with 3D animations. </span>

Motion-Sphere: Visual Representation of the Subtle Motion of Human Joints

Understanding and differentiating subtle human motion over time as sequential data is challenging. We propose Motion-sphere, which is a novel trajectory-based visualization technique, to represent human motion on a unit sphere. Motion-sphere adopts a two-fold approach for human motion visualization, namely a three-dimensional (3D) avatar to reconstruct the target motion and an interactive 3D unit sphere, that enables users to perceive subtle human motion as swing trajectories and color-coded miniature 3D models for twist. This also allows for the simultaneous visual comparison of two motions. Therefore, the technique is applicable in a wide range of applications, including rehabilitation, choreography, and physical fitness training. The current work validates the effectiveness of the proposed work with a user study in comparison with existing motion visualization methods. Our study’s findings show that Motion-sphere is informative in terms of quantifying the swing and twist movements. The Motion-sphere is validated in threefold ways: validation of motion reconstruction on the avatar, accuracy of swing, twist, and speed visualization, and the usability and learnability of the Motion-sphere. Multiple range of motions from an online open database are selectively chosen, such that all joint segments are covered. In all fronts, Motion-sphere fares well. Visualization on the 3D unit sphere and the reconstructed 3D avatar make it intuitive to understand the nature of human motion.