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TT-SLAM: Dense Monocular SLAM for Planar Environments
Abstract : This paper proposes a novel visual SLAM method with dense planar reconstruction using a monocular camera: TT-SLAM. The method exploits planar template-based trackers (TT) to compute camera poses and reconstructs a multiplanar scene representation. Multiple homographies are estimated simultaneously by clustering a set of template trackers supported by superpixelized regions. Compared to RANSACbased multiple homographies method [1], data association and keyframe selection issues are handled by the continuous nature of template trackers. A non-linear optimization process is applied to all the homographies to improve the precision in pose estimation. Experiments show that the proposed method outperforms RANSAC-based multiple homographies method [1] as well as other dense method SLAM techniques such as LSD-SLAM or DPPTAM, and competes with keypointbased techniques like ORB-SLAM while providing dense planar reconstructions of the environment.
https://hal.inria.fr/hal-03169199
Contributor : Eric Marchand Connect in order to contact the contributor
Submitted on : Monday, March 15, 2021 - 10:50:04 AM
Last modification on : Friday, April 8, 2022 - 4:08:03 PM
Long-term archiving on: : Wednesday, June 16, 2021 - 6:29:51 PM
Contributor : Eric Marchand Connect in order to contact the contributor
Submitted on : Monday, March 15, 2021 - 10:50:04 AM
Last modification on : Friday, April 8, 2022 - 4:08:03 PM
Long-term archiving on: : Wednesday, June 16, 2021 - 6:29:51 PM
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2021_icra_wang.pdf
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