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Semantic Visual Localization
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionRobust visual localization under a wide range of viewing conditions is a fundamental problem in computer vision. Handling the difficult cases of this problem is not only very challenging but also of high practical relevance, e.g., in the context of life-long localization for augmented reality or autonomous robots. In this paper, we propose a novel approach based on a joint 3D geometric and semantic understanding of the world, enabling it ...Conference Paper -
Real-Time Dense Mapping for Self-Driving Vehicles using Fisheye Cameras
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Toroidal Constraints for Two-Point Localization under High Outlier Ratios
(2017)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos
(2017)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
Direct Visual Odometry for a Fisheye-Stereo Camera
(2017)2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Conference Paper -
Towards Robust Visual Odometry with a Multi-Camera System
(2018)2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)We present a visual odometry (VO) algorithm for a multi-camera system and robust operation in challenging environments. Our algorithm consists of a pose tracker and a local mapper. The tracker estimates the current pose by minimizing photometric errors between the most recent keyframe and the current frame. The mapper initializes the depths of all sampled feature points using plane-sweeping stereo. To reduce pose drift, a sliding window ...Conference Paper