ABSTRACT
Mobile Augmented Reality (AR) provides immersive experiences by aligning virtual content (holograms) with a view of the real world. When a user places a hologram it is usually expected that like a real object, it remains in the same place. However, positional errors frequently occur due to inaccurate environment mapping and device localization, to a large extent determined by the properties of natural visual features in the scene. In this demonstration we present SceneIt, the first visual environment rating system for mobile AR based on predictions of hologram positional error magnitude. SceneIt allows users to determine if virtual content placed in their environment will drift noticeably out of position, without requiring them to place that content. It shows that the severity of positional error for a given visual environment is predictable, and that this prediction can be calculated with sufficiently high accuracy and low latency to be useful in mobile AR applications.
- Apple. 2021. ARKit. https://developer.apple.com/augmented-reality/Google Scholar
- Lillemor Blom. 2018. Impact of light on augmented reality. Master's thesis. Linköping University.Google Scholar
- Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang. 2017. Matterport3D: Learning from RGB-D data in indoor environments. In International Conference on 3D Vision (3DV) 2017.Google ScholarCross Ref
- FastAPI. 2021. FastAPI. https://fastapi.tiangolo.com/Google Scholar
- James Garforth and Barbara Webb. 2019. Visual appearance analysis of forest scenes for monocular SLAM. In IEEE ICRA 2019.Google ScholarCross Ref
- Google. 2021. ARCore. https://arvr.google.com/arcore/Google Scholar
- Li Jinyu, Yang Bangbang, Chen Danpeng, Wang Nan, Zhang Guofeng, and Bao Hujun. 2019. Survey and evaluation of monocular visual-inertial SLAM algorithms for augmented reality. Virtual Reality & Intelligent Hardware 1, 4 (2019), 386--410.Google ScholarCross Ref
- Alexandre Morgand and Mohamed Tamaazousti. 2014. Generic and real-time detection of specular reflections in images. In VISAPP 2014.Google Scholar
- Xukan Ran, Carter Slocum, Maria Gorlatova, and Jiasi Chen. 2019. ShareAR: Communication-efficient multi-user mobile augmented reality. In ACM HotNets 2019.Google Scholar
- Christoph Redies, Seyed Ali Amirshahi, Michael Koch, and Joachim Denzler. 2012. PHOG-derived aesthetic measures applied to color photographs of artworks, natural scenes and objects. In ECCV 2012.Google ScholarDigital Library
- Joseph Redmon and Ali Farhadi. 2018. YOLOv3: An incremental improvement. arXiv preprint arXiv:1804.02767 (2018).Google Scholar
- Brian D Ripley. 1976. The second-order analysis of stationary point processes. Journal of Applied Probability 13, 2 (1976), 255--266.Google ScholarCross Ref
- Edward Rosten and Tom Drummond. 2006. Machine learning for high-speed corner detection. In ECCV 2006.Google ScholarDigital Library
- C. E. Shannon. 1948. A mathematical theory of communication. The Bell System Technical Journal 27, 3 (1948), 379--423.Google ScholarCross Ref
- Unity. 2021. Unity AR Foundation. https://unity.com/unity/features/arfoundation/Google Scholar
- Reid Vassallo, Adam Rankin, Elvis C. S. Chen, and Terry M. Peters. 2017. Hologram stability evaluation for Microsoft HoloLens. In SPIE Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment.Google Scholar
- Yichin Wu, Liwei Chan, and Wen-Chieh Lin. 2019. Tangible and visible 3D object reconstruction in augmented reality. In IEEE ISMAR 2019.Google ScholarCross Ref
- Xin Yang, Haiyang Mei, Ke Xu, Xiaopeng Wei, Baocai Yin, and Rynson WH Lau. 2019. Where is my mirror?. In IEEE ICCV 2019.Google ScholarCross Ref
- Honghai Yu and Stefan Winkler. 2013. Image complexity and spatial information. In IEEE QoMEX 2013.Google ScholarCross Ref
Index Terms
- Will it Move?: Indoor Scene Characterization for Hologram Stability in Mobile AR
Recommendations
Invisible Textures: Comparing Machine and Human Perception of Environment Texture for AR
ImmerCom '23: Proceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and SystemsMobile augmented reality (AR) has a wide range of promising applications, but its efficacy is subject to the impact of environment texture on both machine and human perception. Performance of the machine perception algorithm underlying accurate ...
MagicBook: transitioning between reality and virtuality
CHI EA '01: CHI '01 Extended Abstracts on Human Factors in Computing SystemsThe MagicBook explores how interfaces can be developed that allow for seamless transition between Physical Reality, Augmented Reality (AR), and immersive Virtual Reality (VR) in a collaborative setting. The MagicBook is a normal book and can be read ...
Haptics in Augmented Reality
ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2An augmented reality system merges synthetic sensory information into a user's perception of a three-dimensional environment. An important performance goal for an augmented reality system is that the user perceives a single seamless environment. In most ...
Comments