Development of Anatomy Learning System based on Augmented Reality
Shruti Bhatla, Vikas Tripathi · 2021
Computer vision is a multidisciplinary field that allows the digital world to interact with the real world by performing a detailed image analysis so that it can predict the visual input like human brain. It has massively impacted every single domain from retail to agriculture, sports to education and military to medical field. It is the foundation for many evolving technologies. One of such promising technology is Augmented Reality (AR). AR has capability to merge digitally generated images and texts with actual environment. AR technologies have helped us in various sectors and can be used to enhance learning by facilitating one to completely comprehend a theoretical concept by representing a three-dimensional visualization through an intuitive model. In contrast to this human anatomical structures are usually difficult to learn because of constraint to envision those structures from 2D image into 3D. So, this paper presents a methodology which is involved in developing an anatomy learning framework using AR. The system generates a 3D model of human skeletal system on the 2D image using image processing, pattern recognition and feature detection algorithms. The accuracy of the framework in processing the image and rendering of model comes out to be 76.8%. The system aims to help by visualizing the complex anatomical structures more easily and improving our perception of feeling natural environments in new and enhanced forms.