Publications

We propose a novel approach that simultaneously solves the problems of counting, density map estimation and localization of people in a given dense crowd image. We also introduce the largest crowd counting dataset (UCF-QNRF dataset) that overcomes the shortcomings of previous datasets, and contains 1.25 million humans manually marked with dot annotations.

15th European Conference on Computer Vision (ECCV), 2018

In this paper, we propose a computer vision based framework that automatically analyses video sequence and computes important measurements which include estimation of crowd density, identification of dominant patterns, detection and localization of congestion

17th Scientific Meeting on Hajj & Umrah Research, 2017