ANALYSIS AND EVALUATION OF FEATURE DETECTION AND TRACKING TECHNIQUES USING OPENCV WITH FOCUS ON MARKERLESS AUGMENTED REALITY APPLICATIONS

Authors

  • GUSTAVO MAGALHÃES MOURA Computer Science Department, Federal University of Juiz de Fora Juiz de Fora, Minas Gerais, 36036-900, Brazil
  • RODRIGO LUIS DE SOUZA DA SILVA Computer Science Department, Federal University of Juiz de Fora Juiz de Fora, Minas Gerais, 36036-900, Brazil

Keywords:

Augmented Reality, OpenCV, feature detector

Abstract

Augmented Reality (AR) is a technology able to extend human interactions with the real world. One field of study in AR is the use of real objects as markers. To perform this task, feature recognition of the real world by computer systems must be performed. This work consists in the analysis and evaluation of several algorithms available in OpenCV library that allow the detection of pre-established patterns in images and videos. The main contribution of this work is to present the most appropriate combination of algorithms to help the development of markerless AR applications.

 

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Published

2017-02-27

How to Cite

MOURA, G. M., & DA SILVA, R. L. D. S. . (2017). ANALYSIS AND EVALUATION OF FEATURE DETECTION AND TRACKING TECHNIQUES USING OPENCV WITH FOCUS ON MARKERLESS AUGMENTED REALITY APPLICATIONS. Journal of Mobile Multimedia, 12(3-4), 291–302. Retrieved from https://journals.riverpublishers.com/index.php/JMM/article/view/4473

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