Video Object Tracking by Feature Point Descriptor and Template Matching

Authors

  • Andrés Ely Pat-Chan Tecnológico Nacional de México / IT de Mérida
  • Francisco Javier Hernandez-Lopez Centro de Investigación en Matemáticas, A.C.
  • Mario Renán Moreno-Sabido Tecnológico Nacional de México / IT de Mérida

DOI:

https://doi.org/10.13053/cys-29-3-4806

Keywords:

Video object tracking, template matching, feature point descriptors, deep learning

Abstract

The present research focuses on developing a method based on feature point descriptors and template matching and comparing its performance with a method based on deep learning. These methods have particular aspects in how they were implemented; some stand out for the simplicity of their structure and others for the complexity they entail. The methods presented in this work range from developing a basic template matching algorithm, developing an algorithm based on feature point descriptors incorporating the template matching qualities to obtain better results, to implementing a method based on deep learning. Performance and precision tests are carried out to compare the methods on a selected dataset of video object tracking.

Author Biographies

Andrés Ely Pat-Chan, Tecnológico Nacional de México / IT de Mérida

Andrés E. Pat-Chan received a B.E. degree in Computer Systems Engineering from the Mérida Institute of Technology, México, in 2018. He has collaborated and participated in academic research programs, publication of scientific articles, and presentations at various universities in México. He is currently collaborating on scientific projects at the Center for Research in Mathematics (CIMAT) in Mérida Yucatán, México. His main interests lie in artificial intelligence and computer vision projects. He was a scholarship recipient from the National Council of Humanities, Science, and Technologies (CONAHCYT).

Francisco Javier Hernandez-Lopez, Centro de Investigación en Matemáticas, A.C.

Francisco J. Hernandez-Lopez received a B.E. degree in Computer Systems Engineering from the San Luis Potosí Institute of Technology, México, in 2005. He received the M.Sc. and D.Sc. degrees in Computer Science from the Center for Research in Mathematics (CIMAT), México, in 2009 and 2014 respectively. He made a postdoctoral stay in CIMAT and he carried out consulting activities in image and video processing. Since 2014, he has been in the Computer Science Department at the CIMAT-Mérida, Yucatán, México. His main interests are in the areas of computer vision, image and video processing, parallel computing, and machine learning. He is a fellow of the National System of Researchers (SNI) of the Mexican Government. [http://www.cimat.mx/~fcoj23/]

Mario Renán Moreno-Sabido, Tecnológico Nacional de México / IT de Mérida

Mario R. Moreno-Sabido obtained a Master of Science degree with a specialty in Computer Systems from the University of the Americas Puebla. He is currently a Full-Time Professor at the Technological Institute of Mérida. His main areas of interest are Learning Environments and Software Engineering.

Downloads

Published

2025-09-25

Issue

Vol. 29 No. 3 (2025): Vol 29 No 3 (2025)

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.