Correspondence-Free Determination of the Affine Fundamental Matrix
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image restoration based on Laplacian preprocessed long-range correlation
Multidimensional Systems and Signal Processing
Comparative study of 3d face acquisition techniques
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Which stereo matching algorithm for accurate 3d face creation ?
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Real-time stereo vision on a reconfigurable system
SAMOS'05 Proceedings of the 5th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
| Hi-index | 0.00 |
We measured the performance of several area-based stereo matching algorithms with noise added to synthetic images. Dense disparity maps were computed and compared with the ground truth using three metrics: the fraction of correctly computed disparities, the mean and standard deviation of the distribution of disparity errors.For a noise-free image, Birch.eld and Tomasi's Pixel-to-Pixel 驴 a dynamic algorithm 驴 performed slightly better than a simple sum-of-absolute differences algorithm (67% correct matches vs 65%) - considered to be within experimental error. A Census algorithm performed worst at only 54%. The dynamic algorithm performed well until the S/N ratio reached 36dB after which its performance started to drop. However, with correctly chosen parameters, it was superior to correlation and Census algorithms until the images became very noisy (~ 15dB). The dynamic algorithm also ran faster than the fastest correlation algorithms using an optimum window radius of 4 and more than 10 times faster than the Census algorithm.