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We propose consensus-making algorithms to acquire viewpoint-invariant GRR.
The consensus-making algorithms serve to acquire viewpoint-invariant GRRs under conditions in which occlusion and object appearance changes occur.
This study used a qualitative design, using focus groups as a vehicle for acquiring the viewpoints of many respondents in a short period of time.
Combining datasets acquired from different viewpoints can potentially provide a full 3D topographic model.
Laser Range Finders are particularly well suited for generating dense 3D maps by aligning multiples scans acquired from different viewpoints.
In Figure 12 we display the surface, acquired from different viewpoints, used as a test for this scenario.
The two acquired stereo camera viewpoints (captured by the cameras located on two sides) were combined using a stereophotogrammetry technique which produced a single 3D image.
In this paper, we propose consensus-making algorithms to acquire a viewpoint-invariant representation of the geometric relation, which is an unaddressed issue in the HIPM.
We simulated realistic scenarios where the multiple views could have been acquired from fairly different viewpoints: 1. Same view setting, θ test = θ train.
Although these methods obtained good performance, generally they need be made an explicit or implicit assumption that the training and testing samples have identical or similar orientations or are acquired from the same viewpoint [8].
More and more attention has been paid to the invariant texture analysis, because the training and testing samples generally have not identical or similar orientations, or are not acquired from the same viewpoint in many practical applications, which often has negative influences on texture analysis.
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