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Pose Estimation for Augmented Reality: A Hands-On Survey

Published: 01 December 2016 Publication History

Abstract

Augmented reality (AR) allows to seamlessly insert virtual objects in an image sequence. In order to accomplish this goal, it is important that synthetic elements are rendered and aligned in the scene in an accurate and visually acceptable way. The solution of this problem can be related to a pose estimation or, equivalently, a camera localization process. This paper aims at presenting a brief but almost self-contented introduction to the most important approaches dedicated to vision-based camera localization along with a survey of several extension proposed in the recent years. For most of the presented approaches, we also provide links to code of short examples. This should allow readers to easily bridge the gap between theoretical aspects and practical implementations.

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  • (2024)Synthetic Data for Deep Learning in Computer Vision & Medical Imaging: A Means to Reduce Data BiasACM Computing Surveys10.1145/366375956:11(1-37)Online publication date: 28-Jun-2024
  • (2024)How Different Is the Perception of Vibrotactile Texture Roughness in Augmented versus Virtual Reality?Proceedings of the 30th ACM Symposium on Virtual Reality Software and Technology10.1145/3641825.3687738(1-10)Online publication date: 9-Oct-2024
  • (2024)Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2021.313630146:3(1788-1803)Online publication date: 1-Mar-2024
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cover image IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics  Volume 22, Issue 12
December 2016
145 pages

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IEEE Educational Activities Department

United States

Publication History

Published: 01 December 2016

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Cited By

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  • (2024)Synthetic Data for Deep Learning in Computer Vision & Medical Imaging: A Means to Reduce Data BiasACM Computing Surveys10.1145/366375956:11(1-37)Online publication date: 28-Jun-2024
  • (2024)How Different Is the Perception of Vibrotactile Texture Roughness in Augmented versus Virtual Reality?Proceedings of the 30th ACM Symposium on Virtual Reality Software and Technology10.1145/3641825.3687738(1-10)Online publication date: 9-Oct-2024
  • (2024)Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2021.313630146:3(1788-1803)Online publication date: 1-Mar-2024
  • (2024)Active Vision-Based Finite-Time Trajectory-Tracking Control of an Unmanned Surface Vehicle Without Direct Position MeasurementsIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.336477025:9(12151-12162)Online publication date: 22-Feb-2024
  • (2024)NVR-Net: Normal Vector Guided Regression Network for Disentangled 6D Pose EstimationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.329061734:2(1098-1113)Online publication date: 1-Feb-2024
  • (2024)Absolute Pose Estimation With a Known Direction by Motion DecouplingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.326445134:7(5215-5228)Online publication date: 1-Jul-2024
  • (2024)A robust direct linear transformation for camera pose estimation using pointsImage and Vision Computing10.1016/j.imavis.2023.104883141:COnline publication date: 1-Jan-2024
  • (2024)Server-enabled mixed reality for flood risk communicationEnvironmental Modelling & Software10.1016/j.envsoft.2024.106054177:COnline publication date: 1-Jun-2024
  • (2024)A fast, lightweight deep learning vision pipeline for autonomous UAV landing support with added robustnessEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.107864131:COnline publication date: 1-May-2024
  • (2024)A new method for repeated localization and matching of tunnel lining defectsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.107855132:COnline publication date: 1-Jun-2024
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