Chapter 8 Future Work
8.3 Intelligence tools for more applications
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8.2 Parameter estimation
In Chapter 3 and Chapter 4, we also discussed several parameter estimation algorithms and proposed some robust methods. For the fitness function in the proposed parameter estimation methods, it is decided by a geometric distance. However, one may use multi-objective functions as the fitness function to getting more robustness. We believe that the similarity of the corresponding points can be one of the multi-objective functions. This could be explored in the future.
Furthermore, various variant parameter estimation algorithms have been proposed in recent years. Each method has its own advantages as well as disadvantages. Finding a more robust algorithm by combining the existing methods or cooperated with a new method is also a challenging and interesting work.
8.3 Intelligence tools for more applications
The proposed guidelines can help us to avoid degeneracies in multi-view image processing. It is useful for improving the estimation of the corresponding points and the geometries in multi-view images. We can use the guidelines to analyze and improve the multi-view image applications, such as 3D reconstruction, image inpainting, object tracking, etc. One may also try to explore more problems which will influence the accuracy. The degeneracies and the parameter estimation methods could be considered together for the multi-view image applications in the future.
Moreover, the multi-view geometry plays an important role in many researches and applications in the field of robotics. For example, the simultaneous localization and mapping (SLAM) [21][63] need accurate 3D reconstruction technologies in constructing the 3D
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environments. Figure 8-1 shows an example of the map built by SLAM. The constructed environment is also helpful for the surveillance applications. Some of the applications in robotics use the SfM to build such environments. There are many challenges and further research issues of these kinds.
Figure 8-1 An example of the simultaneous localization and mapping [63].
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