Augmented Reality Applications Enabled by Computer Vision Technologies

EasyChair Preprint 12354

Abstract

This paper explores the diverse landscape of AR applications enabled by computer vision technologies, highlighting their significance, challenges, and potential impact on reshaping human-computer interaction. The paper begins by elucidating the foundational principles of augmented reality and computer vision, outlining how computer vision techniques such as object detection, pose estimation, and depth sensing enable AR systems to understand and interact with the physical world. It discusses the evolution of AR technologies, from marker-based approaches to marker less and spatially-aware AR experiences, driven by advancements in computer vision algorithms and hardware capabilities. Furthermore, the paper explores a wide range of AR applications across various domains, including gaming, education, healthcare, retail, and industrial training. It showcases case studies and research findings that demonstrate the transformative potential of AR in enhancing learning experiences, improving medical diagnostics and treatment, revolutionizing retail shopping experiences, and optimizing industrial workflows.

Keyphrases: Technologies, computer, vision

@booklet{EasyChair:12354,
  author    = {Julia Anderson and Robert Thomas},
  title     = {Augmented Reality Applications Enabled by Computer Vision Technologies},
  howpublished = {EasyChair Preprint 12354},
  year      = {EasyChair, 2024}}