TY - GEN
T1 - Comparison of person tracking algorithms using overhead view implemented in OpenCV
AU - Ullah, Kaleem
AU - Ahmed, Imran
AU - Ahmad, Misbah
AU - Khan, Iqbal
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - As computer based technologies are growing rapidly, new problems are arising, which need serious and urgent attentions. Person tracking is one of the typical computer vision problem which is the center of interest for researchers working on surveillance systems (industries, shopping malls, educational institutions and hospitals etc. In this research work, a top view camera has been installed with a wide angle lens able to cover a wide area and more information for surveillance and visual monitoring purposes. Some of the common issues that are addressed in this research work are occlusion, sudden change in movement, tracking standstill body, abrupt change in direction, varying lightening conditions and differentiating a person from other objects. In this paper, different tracking algorithms are compared on a newly developed dataset using OpenCV. These algorithms are pre-implemented in the popular OpenCV library. The results and efficiency of these algorithms on a new data set are also discussed. All these algorithms give different results on overhead and frontal view video sequences.
AB - As computer based technologies are growing rapidly, new problems are arising, which need serious and urgent attentions. Person tracking is one of the typical computer vision problem which is the center of interest for researchers working on surveillance systems (industries, shopping malls, educational institutions and hospitals etc. In this research work, a top view camera has been installed with a wide angle lens able to cover a wide area and more information for surveillance and visual monitoring purposes. Some of the common issues that are addressed in this research work are occlusion, sudden change in movement, tracking standstill body, abrupt change in direction, varying lightening conditions and differentiating a person from other objects. In this paper, different tracking algorithms are compared on a newly developed dataset using OpenCV. These algorithms are pre-implemented in the popular OpenCV library. The results and efficiency of these algorithms on a new data set are also discussed. All these algorithms give different results on overhead and frontal view video sequences.
KW - Computer Vision
KW - OpenCV.
KW - Person tracking
KW - Top view
KW - Video surveillance
UR - http://www.scopus.com/inward/record.url?scp=85074905788&partnerID=8YFLogxK
U2 - 10.1109/IEMECONX.2019.8877025
DO - 10.1109/IEMECONX.2019.8877025
M3 - Conference contribution
AN - SCOPUS:85074905788
T3 - IEMECON 2019 - 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference
SP - 284
EP - 289
BT - IEMECON 2019 - 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference
A2 - Chakrabarti, Satyajit
A2 - Mukherjee, Aniruddha
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference, IEMECON 2019
Y2 - 13 March 2019 through 15 March 2019
ER -