5 papers
Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition
M. Usman Maqbool Bhutta, Yuxiang Sun, Darwin Lau +1
Deep learning-based image retrieval techniques for the loop closure detection demonstrate satisfactory performance. However, it is still challenging to achieve high-level performan…
Smart-Inspect: Micro Scale Localization and Classification of Smartphone Glass Defects for Industrial Automation
M Usman Maqbool Bhutta, Shoaib Aslam, Peng Yun +2
The presence of any type of defect on the glass screen of smart devices has a great impact on their quality. We present a robust semi-supervised learning framework for intelligent…
Loop-box: Multi-Agent Direct SLAM Triggered by Single Loop Closure for Large-Scale Mapping
M Usman Maqbool Bhutta, Manohar Kuse, Rui Fan +2
In this paper, we present a multi-agent framework for real-time large-scale 3D reconstruction applications. In SLAM, researchers usually build and update a 3D map after applying no…
PCR-Pro: 3D Sparse and Different Scale Point Clouds Registration and Robust Estimation of Information Matrix For Pose Graph SLAM
M. Usman Maqbool Bhutta, Ming Liu
For both indoor and outdoor environments, we propose an efficient and novel method for different scales and sparse 3D point clouds registration that cannot be handled by the curren…
Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation
Han Ma, Yixin Ma, Jianhao Jiao +5
Lane detection is very important for self-driving vehicles. In recent years, computer stereo vision has been prevalently used to enhance the accuracy of the lane detection systems.…