Fig 6 - uploaded by Sarvesh Kumar Singh
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(a) An ordered point cloud with point transitions shown using a colour scale, (b) point cloud coloured with respect to range showing the variability of 3DUID points with respect to surrounding points, (c) concept of point angle showing the angle of point transition with respect to the nearest sensor location. Transition point shown in red denotes that after this point transition from wall to 3DUID occur. (d) Some of the spurious points encountered in the void region of 3DUID due to sensor range inaccuracy.

(a) An ordered point cloud with point transitions shown using a colour scale, (b) point cloud coloured with respect to range showing the variability of 3DUID points with respect to surrounding points, (c) concept of point angle showing the angle of point transition with respect to the nearest sensor location. Transition point shown in red denotes that after this point transition from wall to 3DUID occur. (d) Some of the spurious points encountered in the void region of 3DUID due to sensor range inaccuracy.

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Spatially and geometrically accurate laser scans are essential in modelling infrastructure for applications in civil, mining and transportation. Monitoring of underground or indoor environments such as mines or tunnels is challenging due to unavailability of a sensor positioning framework, complicated structurally symmetric layouts, repetitive feat...

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Context 1
... an ordered point cloud, a uniform transition between points, shown with a colour scale, can be observed (Fig. 6a). Also, the range values of all the points lying on the 3DUID are deemed to vary considerably when compared to other points in the surrounding (Fig. 6b). In Fig. 6c, θ1 represents the point angle between transition point P1' on the wall and P2' on the 3DUID whereas θ2 represents the point angle between points P1 and P2 on the 3DUID. ...
Context 2
... an ordered point cloud, a uniform transition between points, shown with a colour scale, can be observed (Fig. 6a). Also, the range values of all the points lying on the 3DUID are deemed to vary considerably when compared to other points in the surrounding (Fig. 6b). In Fig. 6c, θ1 represents the point angle between transition point P1' on the wall and P2' on the 3DUID whereas θ2 represents the point angle between points P1 and P2 on the 3DUID. Geometrically, the angle θ1 will always be small in comparison to θ2 due to offset between 3DUID and wall. A multiple threshold criterion with |ED| > 8 cm, ...
Context 3
... an ordered point cloud, a uniform transition between points, shown with a colour scale, can be observed (Fig. 6a). Also, the range values of all the points lying on the 3DUID are deemed to vary considerably when compared to other points in the surrounding (Fig. 6b). In Fig. 6c, θ1 represents the point angle between transition point P1' on the wall and P2' on the 3DUID whereas θ2 represents the point angle between points P1 and P2 on the 3DUID. Geometrically, the angle θ1 will always be small in comparison to θ2 due to offset between 3DUID and wall. A multiple threshold criterion with |ED| > 8 cm, |R| > 8 cm ...
Context 4
... the known 3DUID dimensions to identify potential 3DUIDs. A tolerance of ± 3 cm in the length and width of the fitted rectangle was set to account for probable sensor range errors. Henceforth, the point cloud cluster of potential 3DUID was divided into 6 cm × 6 cm grids, where the grid with points represented '1' and void of points represented '0' (Fig. 6d). Due to the range uncertainty of the laser scanner some spurious points were encountered in the void region that affected pattern recognition (Fig. 6d). Applying a simple threshold, efficiently helped in overcoming this issue and the pattern was simply decoded through binary conversion. Whenever there were less than 20 points in a grid ...
Context 5
... sensor range errors. Henceforth, the point cloud cluster of potential 3DUID was divided into 6 cm × 6 cm grids, where the grid with points represented '1' and void of points represented '0' (Fig. 6d). Due to the range uncertainty of the laser scanner some spurious points were encountered in the void region that affected pattern recognition (Fig. 6d). Applying a simple threshold, efficiently helped in overcoming this issue and the pattern was simply decoded through binary conversion. Whenever there were less than 20 points in a grid it was considered '0' or else '1'. Upon matching of binary pattern with the installed 3DUID patterns, the point cloud of 3DUID and the corresponding ...

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