eprintid: 4258
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/42/58
datestamp: 2023-11-09 16:15:55
lastmod: 2023-11-09 16:15:55
status_changed: 2023-11-09 15:58:02
type: conference_item
metadata_visibility: show
creators_name: Yussiff, A.-L.
creators_name: Yong, S.-P.
creators_name: Baharudin, B.B.
title: Parallel Kalman filter-based multi-human tracking in surveillance video
ispublished: pub
keywords: Computer graphics; Computer graphics equipment; Graphics processing unit; Program processors; Security systems; Target tracking, Human Tracking; Kalman filtering algorithms; Multi-human tracking; Multi-person tracking; Multiple target tracking; Parallel implementations; Parallel-computing environment; Standard Kalman filters, Kalman filters
note: cited By 6; Conference of 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:112912
abstract: A novel approach to robust and flexible person tracking using an algorithm that integrates state of the arts techniques; an Enhanced Person Detector (EPD) and Kalman filtering algorithm. This proposed algorithm employs multiple instances of Kalman Filter with complex assignment constraints using Graphics Processing Unit (GPU-NVDIA CUDA) as a parallel computing environment for tracking multiple persons even in the presence of occlusion. A Kalman filter is a recursive algorithm which predict the state variables and further uses the observed data to correct the predicted value. Data association in different frames are solved using Hungarian technique to link data in previous frame to the current frame. The benefit of this research is an adoption of standard Kalman Filter for multiple target tracking of humans in real time. This can further be used in all applications where human tracking is needed. The parallel implementation has increased the frame processing speed by 20-30 percent over the CPU implementation. © 2014 IEEE.
date: 2014
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938777988&doi=10.1109%2fICCOINS.2014.6868359&partnerID=40&md5=5c6738c8ed0d3d423c2955feac8198be
id_number: 10.1109/ICCOINS.2014.6868359
full_text_status: none
publication: 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
refereed: TRUE
isbn: 9781479943913
citation:   Yussiff, A.-L. and Yong, S.-P. and Baharudin, B.B.  (2014) Parallel Kalman filter-based multi-human tracking in surveillance video.  In: UNSPECIFIED.