2015 IEEE International Symposium on Mixed and Augmented Reality Workshops 2015
DOI: 10.1109/ismarw.2015.16
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Efficient Use of Textured 3D Model for Pre-observation-based Diminished Reality

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Cited by 18 publications
(22 citation statements)
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“…Various types of images are used as follows: Internet photos [13], X-ray images [8,24], image sets actively [25,26], streaming image sequences from surveillance cameras [27], multi-view cameras [6,[28][29][30], and RGB-D cameras [31,32]. One could store a sufficient number of viewpoints when one carefully captures a scene during enough time [13,25,26]. However, one will suffer from the geometric or photometric differences between the real and virtual scenes in the DR results due to the intervals between the preliminary observation and the current DR experience.…”
Section: Background Observation Observe Backgrounds Tomentioning
confidence: 99%
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“…Various types of images are used as follows: Internet photos [13], X-ray images [8,24], image sets actively [25,26], streaming image sequences from surveillance cameras [27], multi-view cameras [6,[28][29][30], and RGB-D cameras [31,32]. One could store a sufficient number of viewpoints when one carefully captures a scene during enough time [13,25,26]. However, one will suffer from the geometric or photometric differences between the real and virtual scenes in the DR results due to the intervals between the preliminary observation and the current DR experience.…”
Section: Background Observation Observe Backgrounds Tomentioning
confidence: 99%
“…However, minimizing the ROI will reduce unnecessary artifacts while such rigorous edges may make the hidden area conspicuous. Geometric models of the target objects to be removed [25], simple 3D bounding boxes [6,26], and image recognition techniques [13,39] are used to detect the ROI. Several methods place the target objects in a non-reconstruction area not to be appeared in the resulting image [30,40].…”
Section: Background Observation Observe Backgrounds Tomentioning
confidence: 99%
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