20 citations · 55 across the 14 of their papers we have counts for
14 papers
TextSLAM: Visual SLAM with Semantic Planar Text Features
Boying Li, Danping Zou, Yuan Huang +3
We propose a novel visual SLAM method that integrates text objects tightly by treating them as semantic features via fully exploring their geometric and semantic prior. The text ob…
Sky-GVINS: a Sky-segmentation Aided GNSS-Visual-Inertial System for Robust Navigation in Urban Canyons
Jie Yin, Tao Li, Hao Yin +2
Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization so…
FeatureBooster: Boosting Feature Descriptors with a Lightweight Neural Network
Xinjiang Wang, Zeyu Liu, Yu Hu +3
We introduce a lightweight network to improve descriptors of keypoints within the same image. The network takes the original descriptors and the geometric properties of keypoints a…
M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots
Jie Yin, Ang Li, Tao Li +2
We introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera, an…
Multi-instance Point Cloud Registration by Efficient Correspondence Clustering
Weixuan Tang, Danping Zou
We address the problem of estimating the poses of multiple instances of the source point cloud within a target point cloud. Existing solutions require sampling a lot of hypotheses…
StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation
Boying Li, Yuan Huang, Zeyu Liu +2
Self-supervised monocular depth estimation has achieved impressive performance on outdoor datasets. Its performance however degrades notably in indoor environments because of the l…
Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze
Jinquan Li, Ling Pei, Danping Zou +5
This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model…
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors
Fanyi Xiao, Ling Pei, Lei Chu +4
Sensor-based human activity recognition (HAR) is now a research hotspot in multiple application areas. With the rise of smart wearable devices equipped with inertial measurement un…
TextSLAM: Visual SLAM with Planar Text Features
Boying Li, Danping Zou, Daniele Sartori +2
We propose to integrate text objects in man-made scenes tightly into the visual SLAM pipeline. The key idea of our novel text-based visual SLAM is to treat each detected text as a…
Reconstructing 3D Motion Trajectory of Large Swarm of Flying Objects
Danping Zou, Yan Qiu Chen
This paper addresses the problem of reconstructing the motion trajectories of the individuals in a large collection of flying objects using two temporally synchronized and geometri…
StructVIO : Visual-inertial Odometry with Structural Regularity of Man-made Environments
Danping Zou, Yuanxin Wu, Ling Pei +2
We propose a novel visual-inertial odometry approach that adopts structural regularity in man-made environments. Instead of using Manhattan world assumption, we use Atlanta world m…
Efficient Outlier Removal in Large Scale Global Structure-from-Motion
Fei Wen, Danping Zou, Rendong Ying +1
This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deteriorati…
Active Image-based Modeling with a Toy Drone
Rui Huang, Danping Zou, Richard Vaughan +1
Image-based modeling techniques can now generate photo-realistic 3D models from images. But it is up to users to provide high quality images with good coverage and view overlap, wh…
Dynamic Magnetometer Calibration and Alignment to Inertial Sensors by Kalman Filtering
Yuanxin Wu, Danping Zou, Peilin Liu +1
Magnetometer and inertial sensors are widely used for orientation estimation. Magnetometer usage is often troublesome, as it is prone to be interfered by onboard or ambient magneti…