Cross-Modal Semi-Dense 6-DoF Tracking of an Event Camera in Challenging Conditions

• URL: http://arxiv.org/abs/2401.08043v1
• Date: Tue, 16 Jan 2024 01:48:45 GMT
• Title: Cross-Modal Semi-Dense 6-DoF Tracking of an Event Camera in Challenging Conditions
• Authors: Yi-Fan Zuo, Wanting Xu, Xia Wang, Yifu Wang, Laurent Kneip
• Abstract summary: Event-based cameras are bio-inspired visual sensors that perform well in HDR conditions and have high temporal resolution. The present work demonstrates the feasibility of purely event-based tracking if an alternative sensor is permitted for mapping. The method relies on geometric 3D-2D registration of semi-dense maps and events, and achieves highly reliable and accurate cross-modal tracking results.
• Score: 29.608665442108727
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Vision-based localization is a cost-effective and thus attractive solution for many intelligent mobile platforms. However, its accuracy and especially robustness still suffer from low illumination conditions, illumination changes, and aggressive motion. Event-based cameras are bio-inspired visual sensors that perform well in HDR conditions and have high temporal resolution, and thus provide an interesting alternative in such challenging scenarios. While purely event-based solutions currently do not yet produce satisfying mapping results, the present work demonstrates the feasibility of purely event-based tracking if an alternative sensor is permitted for mapping. The method relies on geometric 3D-2D registration of semi-dense maps and events, and achieves highly reliable and accurate cross-modal tracking results. Practically relevant scenarios are given by depth camera-supported tracking or map-based localization with a semi-dense map prior created by a regular image-based visual SLAM or structure-from-motion system. Conventional edge-based 3D-2D alignment is extended by a novel polarity-aware registration that makes use of signed time-surface maps (STSM) obtained from event streams. We furthermore introduce a novel culling strategy for occluded points. Both modifications increase the speed of the tracker and its robustness against occlusions or large view-point variations. The approach is validated on many real datasets covering the above-mentioned challenging conditions, and compared against similar solutions realised with regular cameras.

Related papers

• EF-3DGS: Event-Aided Free-Trajectory 3D Gaussian Splatting [76.02450110026747]
  Event cameras, inspired by biological vision, record pixel-wise intensity changes asynchronously with high temporal resolution. We propose Event-Aided Free-Trajectory 3DGS, which seamlessly integrates the advantages of event cameras into 3DGS. We evaluate our method on the public Tanks and Temples benchmark and a newly collected real-world dataset, RealEv-DAVIS.
  arXiv  Detail & Related papers  (2024-10-20T13:44:24Z)
• ESVO2: Direct Visual-Inertial Odometry with Stereo Event Cameras [33.81592783496106]
  Event-based visual odometry aims at solving tracking and mapping sub-problems in parallel. We build an event-based stereo visual-inertial odometry system on top of our previous direct pipeline Event-based Stereo Visual Odometry.
  arXiv  Detail & Related papers  (2024-10-12T05:35:27Z)
• EVIT: Event-based Visual-Inertial Tracking in Semi-Dense Maps Using Windowed Nonlinear Optimization [19.915476815328294]
  Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. This paper proposes the addition of inertial signals in order to robustify the estimation. Our evaluation focuses on a diverse set of real world sequences and comprises a comparison of our proposed method against a purely event-based alternative running at different rates.
  arXiv  Detail & Related papers  (2024-08-02T16:24:55Z)
• 3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera [59.846927201816776]
  This paper introduces the first framework for 3D tracking of two fast-moving and interacting hands from a single monocular event camera. Our approach tackles the left-right hand ambiguity with a novel semi-supervised feature-wise attention mechanism and integrates an intersection loss to fix hand collisions.
  arXiv  Detail & Related papers  (2023-12-21T18:59:57Z)
• EVI-SAM: Robust, Real-time, Tightly-coupled Event-Visual-Inertial State Estimation and 3D Dense Mapping [5.154689086578339]
  We propose EVI-SAM to tackle the problem of 6 DoF pose tracking and 3D reconstruction using monocular event camera. A novel event-based hybrid tracking framework is designed to estimate the pose, leveraging the robustness of feature matching and the precision of direct alignment. To the best of our knowledge, this is the first non-learning work to realize event-based dense mapping.
  arXiv  Detail & Related papers  (2023-12-19T07:39:45Z)
• Implicit Event-RGBD Neural SLAM [54.74363487009845]
  Implicit neural SLAM has achieved remarkable progress recently. Existing methods face significant challenges in non-ideal scenarios. We propose EN-SLAM, the first event-RGBD implicit neural SLAM framework.
  arXiv  Detail & Related papers  (2023-11-18T08:48:58Z)
• Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representation [79.02808071245634]
  Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Event streams are divided into grids in the x-y-t coordinates for both positive and negative polarity, producing a set of pillars as 3D tensor representation. Long memory is encoded in the hidden state of adaptive convLSTMs while short memory is modeled by computing spatial-temporal correlation between event pillars.
  arXiv  Detail & Related papers  (2023-03-17T12:12:41Z)
• Asynchronous Optimisation for Event-based Visual Odometry [53.59879499700895]
  Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range. We focus on event-based visual odometry (VO) We propose an asynchronous structure-from-motion optimisation back-end.
  arXiv  Detail & Related papers  (2022-03-02T11:28:47Z)
• DEVO: Depth-Event Camera Visual Odometry in Challenging Conditions [30.892930944644853]
  We present a novel real-time visual odometry framework for a stereo setup of a depth and high-resolution event camera. Our framework balances accuracy and robustness against computational efficiency towards strong performance in challenging scenarios.
  arXiv  Detail & Related papers  (2022-02-05T13:46:47Z)
• Monocular Quasi-Dense 3D Object Tracking [99.51683944057191]
  A reliable and accurate 3D tracking framework is essential for predicting future locations of surrounding objects and planning the observer's actions in numerous applications such as autonomous driving. We propose a framework that can effectively associate moving objects over time and estimate their full 3D bounding box information from a sequence of 2D images captured on a moving platform.
  arXiv  Detail & Related papers  (2021-03-12T15:30:02Z)
• Event-based Stereo Visual Odometry [42.77238738150496]
  We present a solution to the problem of visual odometry from the data acquired by a stereo event-based camera rig. We seek to maximize thetemporal consistency of stereo event-based data while using a simple and efficient representation.
  arXiv  Detail & Related papers  (2020-07-30T15:53:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.