activity
20192024
most citedGood Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency

66 citations · 98 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2024★ 1 cited

OmniPose6D: Towards Short-Term Object Pose Tracking in Dynamic Scenes from Monocular RGB

Yunzhi Lin, Yipu Zhao, Fu-Jen Chu +6

To address the challenge of short-term object pose tracking in dynamic environments with monocular RGB input, we introduce a large-scale synthetic dataset OmniPose6D, crafted to mi…

cs.CV2022

Long-term Visual Map Sparsification with Heterogeneous GNN

Ming-Fang Chang, Yipu Zhao, Rajvi Shah +3

We address the problem of map sparsification for long-term visual localization. For map sparsification, a commonly employed assumption is that the pre-build map and the later captu…

cs.RO2021★ 10 cited

Image-Based Trajectory Tracking through Unknown Environments without Absolute Positioning

Shiyu Feng, Zixuan Wu, Yipu Zhao +1

This paper describes a stereo image-based visual servoing system for trajectory tracking by a non-holonomic robot without externally derived pose information nor a known visual map…

cs.CV2020★ 7 cited

Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM

Yipu Zhao, Justin S. Smith, Patricio A. Vela

The cost-efficiency of visual(-inertial) SLAM (VSLAM) is a critical characteristic of resource-limited applications. While hardware and algorithm advances have been significantly i…

cs.RO2020★ 1 cited

Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy

Yipu Zhao, Justin S. Smith, Sambhu H. Karumanchi +1

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 wi…

cs.RO2020★ 66 cited

Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency

Yipu Zhao, Patricio A. Vela

Analysis of state-of-the-art VO/VSLAM system exposes a gap in balancing performance (accuracy & robustness) and efficiency (latency). Feature-based systems exhibit good performance…