10 accepted papers
An event camera is a vision sensor that captures pixel-level brightness changes and outputs this information as asynchronous events. These events are primarily generated from geometric structures such as edges, which are sensitive to variations in brightness. In this letter, we aim to leverage line …
Reliable multi-object tracking (MOT) is essential for autonomous systems but remains challenging due to ambiguous object characteristics such as birth, death, and motion models, as well as detector errors including false detections and missed objects. Random finite set (RFS) theory provides a rigoro…
An event camera is a vision sensor that captures pixel-level brightness changes and outputs this information as asynchronous events. These events are primarily generated from geometric structures such as edges, which are sensitive to variations in brightness. In this letter, we aim to leverage this
In this study, we propose an object shape alignment method through a robust optimization scheme for 6-degrees-of-freedom (DOF) object pose compensation. Although the pose estimation of the 3D object by the camera has been rapidly improved in recent years with the development of deep learning, the es…
In this letter, we present an event- and frame-based visual-inertial odometry (VIO) algorithm that fuses frames, events, and inertial measurement in a robust and adaptive manner. Frames from standard cameras provide rich context of the scene at a fixed rate. Event cameras on the other hand asynchron
Event cameras are asynchronous neuromorphic vision sensors with high temporal resolution and no motion blur, offering advantages over standard frame-based cameras especially in high-speed motions and high dynamic range conditions. However, event cameras are unable to capture the overall context of t…
In this letter, we propose a novel method to merge a Gaussian mixture on matrix Lie groups and present its application for a simultaneous localization and mapping problem with symmetric objects. The key idea is to predetermine the weighted mean called a <italic xmlns:mml="http://www.w3.org/1998/Math
In the presence of fast motion, point clouds obtained from mechanical spinning LiDAR can be easily distorted due to the slow scanning speed of the LiDAR. Existing LiDAR-only odometry algorithms generally ignore this distortion or compensate by linearly interpolating the estimated relative motion bet…
In this paper, we propose a novel object-based visual-inertial navigation system fully embedded in a matrix Lie group and built upon the invariant Kalman filtering theory. Specifically, we focus on relative pose measurements of objects and derive an error equation at the associated tangent space. We…
In this paper, we propose a novel filtering-based method that fuses events from a dynamic vision sensor (DVS), images, and inertial measurements to estimate camera poses. A DVS is a bio-inspired sensor that generates events triggered by brightness changes. It can cover the drawbacks of a conventiona…