Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia 2011
DOI: 10.1145/2107596.2107597
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Augmented visualization with natural feature tracking

Abstract: Visualization systems often require large monitors or projection screens to display complex information. Even very sophisticated systems that exhibit complex user interfaces do usually not exploit advanced input and output devices. One of the reasons for that is the high cost of special hardware. This paper introduces Augmented Visualization, an interaction method for projection walls as well as monitors using affordable and widely available hardware such as mobile phones or tablets. The main technical challen… Show more

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Cited by 11 publications
(6 citation statements)
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References 26 publications
(22 reference statements)
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“…The vision-based approach is another markerless solution that relies on computer vision and provides very accurate tracking, although it can be unstable as it depends on natural-feature detection. This method is explained in several papers [17][18][19][20] and is based on keypoint extraction and feature descriptors to calculate the pose estimation. This approach has been applied for the augmentation of the urban environment [21] or in object detection in uncontrolled outdoor environments [22].…”
Section: Tracking Outdoormentioning
confidence: 99%
“…The vision-based approach is another markerless solution that relies on computer vision and provides very accurate tracking, although it can be unstable as it depends on natural-feature detection. This method is explained in several papers [17][18][19][20] and is based on keypoint extraction and feature descriptors to calculate the pose estimation. This approach has been applied for the augmentation of the urban environment [21] or in object detection in uncontrolled outdoor environments [22].…”
Section: Tracking Outdoormentioning
confidence: 99%
“…The app presents a complete marker-less tracking solution (Uchiyama and Marchand, 2012). Our approach is based on the recognition of natural features points (Blanco-Pons et al, 2018;Sörös et al, 2011) which are visible in the environment and image tracking solution. We used our own image of the target as tracker (Figure 3) which fulfills the main conditions to be a good tracker, i.e.…”
Section: Ar App Developmentmentioning
confidence: 99%
“…Whenever the user moves the AR device, the tracking system recalculates the new pose in real time and thus the virtual contents have to remain aligned with the real object. The camera pose is calculated with six degrees of freedom, three translation parameters x, y, z and three orientation parameters yaw, pitch, roll [23].…”
Section: Contextmentioning
confidence: 99%