2019
DOI: 10.1007/978-3-030-12957-6_24
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From Discovery to Exhibition - Recomposing History: Digitizing a Cultural Educational Program Using 3D Modeling and Gamification

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“…For the time being, the mainstream algorithm is to define 3D key points on the object and predict the 2D key points on the image as the intermediate representation of the pose estimation in order to construct the corresponding relationship, and then obtain the object pose by calculating the 2D-3D correspondence relationship between those key points [16,17]. Some researchers have proposed a three-stage approach, in which the coarse-to-fine segmentation is achieved in the first two stages, and the results are fed into the third network, which outputs the vertices of the object's bounding box as a result of the results [18][19][20][21][22][23].…”
Section: Introductionmentioning
confidence: 99%
“…For the time being, the mainstream algorithm is to define 3D key points on the object and predict the 2D key points on the image as the intermediate representation of the pose estimation in order to construct the corresponding relationship, and then obtain the object pose by calculating the 2D-3D correspondence relationship between those key points [16,17]. Some researchers have proposed a three-stage approach, in which the coarse-to-fine segmentation is achieved in the first two stages, and the results are fed into the third network, which outputs the vertices of the object's bounding box as a result of the results [18][19][20][21][22][23].…”
Section: Introductionmentioning
confidence: 99%