Reconstructed intensity image-based loop detection method for event-based visual odometry

Yuming Zhou; Yongjun Yu; Kun Liu; Jiejie Yu

doi:10.1117/12.2680949

8 June 2023 Reconstructed intensity image-based loop detection method for event-based visual odometry

Yuming Zhou, Yongjun Yu, Kun Liu, Jiejie Yu

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127073P (2023) https://doi.org/10.1117/12.2680949
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

Existing methods related to event-based SLAM mostly realize front-end visual odometry function in visual navigation and it is difficult to handle loop closure task directly with accumulated events, in which case a complete SLAM framework is needed to be accomplished. This paper presents a solution to the problem of loop closure detection in real time event-based visual odometry with assistance of reconstructed intensity image. The proposed method selects keyframe in frontend and detects loop closure using calculated bag-of-words from intensity image. While loop closure is detected, the photometric bundle adjustment method is implemented to refine global camera pose and global 3D depth points constraints. The proposed method has been tested in MVSEC event-based stereo datasets with loop information, and successfully detects and corrects loop closure. Experiments have shown that the proposed method can successfully reduce about 50% error triggered by visual odometry in real-time trajectory estimation.

Citation Download Citation

Yuming Zhou, Yongjun Yu, Kun Liu, and Jiejie Yu "Reconstructed intensity image-based loop detection method for event-based visual odometry", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127073P (8 June 2023); https://doi.org/10.1117/12.2680949

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KEYWORDS

Image restoration

Visualization

Cameras

Image quality

Information visualization

Neural networks

Motion estimation

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