2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDMMSP-1.1
Paper Title ATVIO: ATTENTION GUIDED VISUAL-INERTIAL ODOMETRY
Authors Li Liu, Ge Li, Peking University Shenzhen Graduate School, China; Thomas H Li, Peking University, China
SessionMMSP-1: Multimedia Signal Processing
LocationGather.Town
Session Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Poster
Topic Multimedia Signal Processing: Multimedia Environments
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Visual-inertial odometry (VIO) aims to predict trajectory by egomotion estimation. In recent years, end-to-end VIO has made great progress. However, how to handle visual and inertial measurements and make full use of the complementarity of cameras and inertial sensors remains a challenge. In the paper, we propose a novel attention guided deep framework for visual-inertial odometry (ATVIO) to improve the performance of VIO. Specifically, we extraordinarily concentrate on the effective utilization of the Inertial Measurement Unit (IMU) information. Therefore, we carefully design a one-dimension inertial feature encoder for IMU data processing. The network can extract inertial features quickly and effectively. Meanwhile, we should prevent the inconsistency problem when fusing inertial and visual features. Hence, we explore a novel cross-domain channel attention block to combine the extracted features in a more adaptive manner. Extensive experiments demonstrate that our method achieves competitive performance against state-of-the-art VIO methods.