Search results for "Disparity map"
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The Usage of Quadtree in Deep Neural Networks to Represent Data For Navigation From a Monocular Camera
2022
Depth acquisition represents a key element for navigation tasks. It is, therefore, one of the major research topics in computer vision. Many approaches have been developed to address this problem by constructing the depth from series of images. However, there is a minimal case proposing a prediction from a single image, made possible with the emergence of deep learning approaches. The latter makes it possible to consider a reduction in both hardware and computing time costs, which is beneficial for embedded systems. However, network architecture remains a heavy process requiring a lot of GPU memory. Few approaches have proposed addressing this problem by developing lightweight architectures…
3D Map Computation from Historical Stereo Photographs of Florence
2018
The analysis of early photographic sources is fundamental for documenting and understanding the evolution of a city so rich in history and art as Florence. Indeed, by the 1860s several photographers used to work in town, and their images (often obtained through stereoscopic set-ups) can help us to reconstruct Florence in 3D as it was by the time of the Italian unification. The first and most delicate part of such reconstruction process is the computation of disparity maps from the historical stereo pairs. This is a very challenging task for fully-automatic computer vision algorithms, since XIX century photographs are affected by several problems—ranging from superficial damages to asynchron…