Mohbat Tharani
Mohbat Tharani is a Research Assistant in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
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Waseem Abbas
Waseem Abbas was a Research Assistant in Computer Vision Lab (cvlab) at LUMS Syed Babar Ali School of Science and Engineering. Research Interest Waseem received BSc degree from the Islamia University of Bahawalpur, Pakistan. He received the M.S. degree in Electrical Engineering from the Lahore University of Management Sciences with a focus on machine learning…
Water Quality Assessment Using Visual Sensors
Mohbat Tharani, Abdul Wahab Amin, Fezan Rasool, Muhammad Maaz, Murtaza Taj, Abubakr Muhammad Summary In the absence of an effective trash management framework, trash is often illegally dumped in rivers and canals running through urban areas, contaminating freshwater and blocking drainage lines which result in urban floods. When this contaminated water reaches agricultural fields, it…
Summer Internships 2018
The Computer Vision Lab hosted a rigorous summer internship program for undergraduate students. Sophomore, Junior and Senior interns worked for 2 months in the lab, under the supervision of faculty and PhD students. The students worked both individually and in groups, on a range of ideas, from making a campus 3D model to automatic generation…
Ali Hassan
Ali Hassan is a Research Assistant in Computer Vision Lab (cvlab ) at LUMS Syed Babar Ali School of Science and Engineering. Research Interest My main areas of interest are Computer Vision, Machine Learning and Robotics. I am primarily interested in Human Motion Analysis. I am currently working on “Human Body Pose Estimation from Monocular…
Alumni | MS Students | People
M. Ahmed Bhimra
M. Ahmed Bhimra is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
ICASSP2022 -Camera Calibration through Camera Projection Loss
Talha Hanif Butt, Murtaza Taj Abstract: Camera calibration is a necessity in various tasks including 3D reconstruction, hand-eye coordination for a robotic interaction, autonomous driving, etc. In this work we propose a novel method to predict extrinsic (baseline, pitch, and translation), intrinsic (focal length and principal point offset) parameters using an image pair. Unlike existing…