Markerless tracking system for augmented reality in the automotive industry

被引:51
|
作者
Lima, Joao Paulo [1 ,2 ]
Roberto, Rafael [1 ]
Simoes, Francisco [1 ]
Almeida, Mozart [1 ]
Figueiredo, Lucas [1 ]
Teixeira, Joao Marcelo [1 ,2 ]
Teichrieb, Veronica [1 ]
机构
[1] Univ Fed Pernambuco UFPE, Voxar Labs, Ctr Informat CIn, Av Jornalista Anibal Fernandes S-N, BR-50740560 Recife, PE, Brazil
[2] Univ Fed Rural Pernambuco UFRPE, Dept Estat & Informat DEINFO, Rua Dom Manoel de Medeiros S-N, BR-52171900 Recife, PE, Brazil
关键词
Tracking; Augmented reality; Automotive sector; SUPPORT;
D O I
10.1016/j.eswa.2017.03.060
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a complete natural feature based tracking system that supports the creation of augmented reality applications focused on the automotive sector. The proposed pipeline encompasses scene modeling, system calibration and tracking steps. An augmented reality application was built on top of the system for indicating the location of 3D coordinates in a given environment which can be applied to many different applications in cars, such as a maintenance assistant, an intelligent manual, and many others. An analysis of the system was performed during the Volkswagen/ISMAR Tracking Challenge 2014, which aimed to evaluate state-of-the-art tracking approaches on the basis of requirements encountered in automotive industrial settings. A similar competition environment was also created by the authors in order to allow further studies. Evaluation results showed that the system allowed users to correctly identify points in tasks that involved tracking a rotating vehicle, tracking data on a complete vehicle and tracking with high accuracy. This evaluation allowed also to understand the applicability limits of texture based approaches in the textureless automotive environment, a problem not addressed frequently in the literature. To the best of the authors' knowledge, this is the first work addressing the analysis of a complete tracking system for augmented reality focused on the automotive sector which could be tested and validated in a major benchmark like the Volkswagen/ISMAR Tracking Challenge, providing useful insights on the development of such expert and intelligent systems. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:100 / 114
页数:15
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