Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixels Measurement Models

Carlo Dal Mutto, Pietro Zanuttigh, Guido M. Cortelazzo

(Multimedia Technology and Telecommunications Laboratory, University of Padova)


This page contains the supplementary material for the paper "Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixels Measurement Models" by Carlo Dal Mutto, Pietro Zanuttigh and Guido M. Cortelazzo that has been submitted to the IEEE Transaction on Pattern Analysis and Machine Intelligence. Due to the limited space in the paper it is not possible to show all the experimental data and some of the figures in the printed version are too small to appreciate many details of the differences between the results of the various compared methods.

This page contains:


Likelihood Functions behavior

If the embedded video is not supported you can download the video from here


You can download from here an archive containing all the data used for the experimental results. The archive contains the following data folders:





LBP Optimization

You can download from here an archive containing the LBP optimization code.



ML and MAP comparison

These images shows a comparison of the performance of the ML and MAP schemes (Fig. 15 in the paper). Notice how the edge of the bear's ear is much sharper when the MAP method is employed. Furthermore artifacts like the small region pointing up in the upper edge are removed. Also flying pixels in the middle between the foreground and background are not present in the MAP result while some of them are still present after the ML optimization.







These images (Fig. 16 of the paper) contains the output depth maps computed by the proposed approach with the ML and MAP schemes on the 5 different scenes used in the experimental results. The ML depth maps still present some artifacts specially in proximity of edges, while the result of the MAP optimization is much sharper. The ToF data has a resolution of just 176x144, 16 times smaller (4 times in each direction) than the presented output depth maps but still the proposed MAP optimization leads to sharp and precisely located edges.


The discontinuities maps used for the computation of the results in Table 3 are the following (click on the images to view a full-resolution version):

Scene 1 Scene 2 Scene 3 Scene 4 Scene 5


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