2010
DOI: 10.1155/2010/146123
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Handling Occlusions for Robust Augmented Reality Systems

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Cited by 7 publications
(7 citation statements)
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“…Although sensor‐based methods are fast and simple to process, they do not have the high precision required for visualizing underground infrastructures (Karimi, Sadeghi Niaraki, & Hosseini Naveh, 2019). Although, noise elimination using a low pass filter or Kalman filter increases the precision, they do not provide very high precision (Maidi et al., 2010).…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Although sensor‐based methods are fast and simple to process, they do not have the high precision required for visualizing underground infrastructures (Karimi, Sadeghi Niaraki, & Hosseini Naveh, 2019). Although, noise elimination using a low pass filter or Kalman filter increases the precision, they do not provide very high precision (Maidi et al., 2010).…”
Section: Related Workmentioning
confidence: 99%
“…Augmented reality (AR) technology can enhance the visualization and representation of a 3D real‐world object, such as underground infrastructure using mobile phones (Gupta & Lohani, 2014; Schall et al., 2009). Therefore, civil engineers can prevent drilling mistakes in the field (Maidi, Ababsa, & Mallem, 2010). One of the significant requirements for AR is identifying and locating real‐world objects concerning a person's head or a camera (Hoff, Nguyen, & Lyon, 1996).…”
Section: Introductionmentioning
confidence: 99%
“…MR research has identified several solutions (Maidi, Ababsa, and Mallem 2010;Tian, Guan, and Wang 2010) to this issue; however, many rely upon controlled environments, fiducial markers, or detailed knowledge of the environment's geometry. This is not always possible to achieve for MR applications set in large-scale and uncontrolled environments.…”
Section: Visualization Limitationsmentioning
confidence: 99%
“…In, an incremental feature tracking is also applied. In these cases, features inside the marker are detected and tracked.…”
Section: Related Workmentioning
confidence: 99%
“…Compared with the solution in, our solution only uses a single marker, so it minimizes environment adaptation. Furthermore, in contrast to the methods in, our proposal combines an incremental tracking with a tracking based on appearance to offer a robust tracking and avoid drift. Additionally, our design is based on customizable textures that are placed in the frame of the marker, which generates, by default, a uniform distribution of features, that is, it is not scene dependent.…”
Section: Related Workmentioning
confidence: 99%