A Survey of Augmented Reality

By Ronald T. Azuma. 1997

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

CCNet: Criss-Cross Attention for Semantic Segmentation (2018, background): “It has been extensively and actively studied in many recent works and is also critical for various challenging and meaningful applications such as autonomous driving [14], augmented reality [1], and image editing [13].”
Attention to Scale: Scale-Aware Semantic Image Segmentation (2015, background): “Successful image segmentation techniques could facilitate a large group of applications such as image editing [17], augmented reality [3] and self-driving vehicles [22].”
Review of Studies on Technology-Enhanced Language Learning and Teaching (2020, background): “It has three characteristics: interaction in real time, integration of real and virtual worlds, and operation in 3D space [113].”
Enabling Fine-Grained Permissions for Augmented Reality Applications with Recognizers (2013, background): “Azuma surveyed augmented reality, defining it as real-time registration of 3-D overlays on the real world [1], later broadening it to include audio and other senses [2].”
Systematic review and meta-analysis of augmented reality in educational settings (2019, background): “Augmented reality (AR) is an important technology that combines reality with virtuality (Akçayir and Akçayir 2017; Azuma 1997).”
A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges (2021, background): “AR is the technology of superimposing virtual objects upon the real world [155].”
Towards Explainable Shared Control using Augmented Reality (2019, background): “Dating back to the earliest applications of AR in robotics, there have been reports on its efficacy at guiding the control of human operators [16]–[18].”
Visual SLAM algorithms: a survey from 2010 to 2016 (2017, background): “vSLAM algorithms have widely proposed in the field of computer vision, robotics and AR [6].”
Edge Computing for the Internet of Things: A Case Study (2018, background): “and reliability constraints for immersive applications, such as virtual and augmented reality [41], [42].”
Applying Deep Learning in Augmented Reality Tracking (2016, background): “As a man-machine interface technology, AR (Augmented Reality) simply renders virtual information on to real objects [1].”
Lucid touch: a see-through mobile device (2007, background): “An overview of early AR work can be found in [2].”
Learning anatomy via mobile augmented reality: Effects on achievement and cognitive load (2016, background): “One of the new generation technologies, augmented reality (AR), has attracted the attention of educators in recent years due its ability to merge the real and virtual world by combining human senses (e.g., sight, sound, and touch) with virtual objects (Azuma, 1997).”
Operating System Support for Augmented Reality Applications (2013, background): “Azuna surveyed augmented reality, defining it as real-time registration of 3-D overlays on the real world [3], later broadened to include audio and other senses [4].”