A Survey on Tracking Techniques in Augmented Reality based Application

Autor: Archana Mantri, Suryansh Gupta, Amanpreet Kaur, Sidharth Gupta, Reshab Chaudhary
Rok vydání: 2019
Předmět:
Zdroj: 2019 Fifth International Conference on Image Information Processing (ICIIP).
DOI: 10.1109/iciip47207.2019.8985779
Popis: Augmented Reality (AR) is a process where the computerized information is “augment” into the real or the physical world. This helps us in better understanding of the process and has numerous applications. The scope of AR is practically unlimited in today's world and if implemented, would help in solving many complex problems in an easy manner. This paper explains the applications of AR in multiple areas. The paper lays stress on six such major areas where the field of AR is flourished. The important milestones in the history of AR are discussed in this paper. Tracking is one of the thrust areas in the field of AR. A thorough survey is conducted on different types of tracking techniques that are used for development of AR applications. The paper is concluded in the form of comparative analysis between different types of sensor based tracking techniques and vision based tracking techniques. Hybridization of different types of tracking techniques is one of the best solutions for an accurate and robust tracking to meet the stringent requirements of AR applications.
Databáze: OpenAIRE