Wei Gao

Wei Gao

Institute of Automation, Chinese Academy of Sciences School of Artificial Intelligence, University of Chinese Academy of Sciences

Research

Implementation and observability analysis of visual-inertial-wheel odometry with robust initialization and online extrinsic calibration

Published:

Combining camera, IMU and wheel encoder is a wise choice for car positioning because of the low cost and complementarity of the sensors. We propose a novel extended visual-inertial odometry algorithm based on sliding window tightly fusing data from the above three sensors. Firstly we propose an IMU-odometer pre-integration approach utilizing complete IMU [Read More]

Cross-modal Learning for Event-based Semantic Segmentation via Attention Soft Alignment

Published:

By demonstrating robustness in scenarios characterized by high-speed motion and extreme lighting changes, event cameras hold great potential for enhancing the perception reliability of autonomous driving systems. Since its novelty and data sparsity, the progress of event-based algorithms is hindered by the scarcity of high-quality labeled [Read More]

A large-scale dataset for indoor visual localization with high-precision ground truth

Published:

This article presents a challenging new dataset for indoor localization research. We have recorded the whole internal structure of Fengtai Wanda Plaza which is an area of over 15,800 m2 with a Navvis M6 device. The dataset contains 679 RGB-D panoramas and 2,664 query images collected by three different smartphones. [Read More]

BSP-MonoLoc: Basic Semantic Primitives Based Monocular Localization on Roads

Published:

Robust visual localization in traffic scenes is a fundamental problem for self-driving vehicles. However, it is still challenging to achieve accurate localization performance because of drastic viewpoint and illumination changes. To address the issues, we design a novel monocular localization framework based on a [Read More]

Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements

Published:

Unlike loose coupling approaches and the EKF-based approaches in the literature, we propose an optimization-based visual-inertial SLAM tightly coupled with raw Global Navigation Satellite System (GNSS) measurements, a first attempt of this kind in the literature to our knowledge. More specifically, reprojection error, [Read More]

Bidirectional Trajectory Computation for Odometer-Aided Visual-Inertial SLAM

Published:

Odometer-aided visual-inertial SLAM systems typically have a good performance for navigation of wheeled platforms, while they usually suffer from degenerate cases before the first turning. In this paper, firstly we perform an observability analysis w.r.t. the extrinsic parameters before the first turning, which is a [Read More]

Scene-unified image translation for visual localization

Published:

Visual localization is a key technology in the field of 3D robot vision. One of its major difficulties lies in how to deal with the challenges brought by the appearance changes of query images and database images caused by large time spans. Many methods focus on extracting more robust features from images to deal with [Read More]

Boosting image-based localization via randomly geometric data augmentation

Published:

Visual localization is a fundamental problem in computer vision and robotics. Recently, deep learning has shown to be effective for robust monocular localization. Most deep learning-based methods utilize convolution neural network (CNN) to regress global 6 degree-of-freedom (Dof) pose. However, these methods suffer from [Read More]