8 accepted papers
To address the challenge of short-term object pose tracking in dynamic environments with monocular RGB input, we introduce a large-scale synthetic dataset Omni-Pose6D, crafted to mirror the diversity of real-world conditions. We additionally present a benchmarking framework for a comprehensive compa
We address the problem of map sparsification for longterm visual localization. A commonly employed assumption in map sparsification is that the pre-build map and the later capture localization query are consistent. However, this assumption can be easily violated in the dynamic world. Additionally, t…
Simultaneous localization and mapping (SLAM) is a crucial functionality for exploration robots and virtual/augmented reality (VR/AR) devices. However, some of such devices with limited resources cannot afford the computational or memory cost to run full SLAM algorithms. We propose a general client-s…
Visual-inertial SLAM is essential for robot navigation in GPS-denied environments, e.g. indoor, underground. Conventionally, the performance of visual-inertial SLAM is evaluated with open-loop analysis, with a focus on the drift level of SLAM systems. In this paper, we raise the question on the impo…
A local map module is often implemented in modern VO/VSLAM systems to improve data association and pose estimation. Conventionally, the local map contents are determined by co-visibility. While co-visibility is cheap to establish, it utilizes the relatively-weak temporal prior (i.e. seen before, lik…
This paper aims to select features that contribute most to the pose estimation in VO/VSLAM. Unlike existing feature selection works that are focused on efficiency only, our method significantly improves the accuracy of pose tracking, while introducing little overhead. By studying the impact of featu…
This paper tackles a problem in line-assisted VO/VSLAM: accurately solving the least squares pose optimization with unreliable 3D line input. The solution we present is good line cutting, which extracts the most-informative sub-segment from each 3D line for use within the pose optimization formulati…
Statistical similarity measurements, such as mutual information (MI) and normalized mutual information (NMI), show potential in the registration of 2D-image to 3D-range scans collected in urban environments. However 2D-3D registration with these measurements are of limited usage in urban sensing app