30 October 2017 Camera pose estimation for augmented reality in a small indoor dynamic scene
Rawia Frikha, Ridha Ejbali, Mourad Zaied
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Abstract
Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.
© 2017 SPIE and IS&T 1017-9909/2017/$25.00 © 2017 SPIE and IS&T
Rawia Frikha, Ridha Ejbali, and Mourad Zaied "Camera pose estimation for augmented reality in a small indoor dynamic scene," Journal of Electronic Imaging 26(5), 053029 (30 October 2017). https://doi.org/10.1117/1.JEI.26.5.053029
Received: 23 May 2017; Accepted: 6 October 2017; Published: 30 October 2017
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CITATIONS
Cited by 9 scholarly publications and 5 patents.
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KEYWORDS
Cameras

Imaging systems

Image segmentation

Augmented reality

3D modeling

Autoregressive models

Video

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