GPU-based Stereo Matching Algorithm with the Strategy of Population-based Incremental Learning


Dong-Hu Nie, Kyu-Phil Han, Heng-Suk Lee, Journal of Information Processing Systems Vol. 5, No. 2, pp. 105-116, Jun. 2009  

10.3745/JIPS.2009.5.2.105
Keywords: Image filtering, Performance Evaluation, General-Purpose Computation Based on GPU, GPU, Population-Based Incremental Learning
Fulltext:

Abstract

To solve the general problems surrounding the application of genetic algorithms in stereo matching, two measures are proposed. Firstly, the strategy of simplified population-based incremental learning (PBIL) is adopted to reduce the problems with memory consumption search inefficiency£¬and a scheme for controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities. In addition, an alternative version of the proposed algorithm, without the use of a probability vector, is also presented for simpler set-ups. Secondly, programmable graphics-hardware (GPU) consists of multiple multi-processors and has a powerful parallelism which can perform operations in parallel at low cost. Therefore, in order to decrease the running time further, a model of the proposed algorithm, which can be run on programmable graphics-hardware (GPU), is presented for the first time. The algorithms are implemented on the CPU as well as on the GPU and are evaluated by experiments. The experimental results show that the proposed algorithm offers better performance than traditional BMA methods with a deliberate relaxation and its modified version in terms of both running speed and stability. The comparison of computation times for the algorithm both on the GPU and the CPU shows that the former has more speed-up than the latter, the bigger the image size is.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Nie, D., Han, K., & Lee, H. (2009). GPU-based Stereo Matching Algorithm with the Strategy of Population-based Incremental Learning. Journal of Information Processing Systems, 5(2), 105-116. DOI: 10.3745/JIPS.2009.5.2.105.

[IEEE Style]
D. Nie, K. Han, H. Lee, "GPU-based Stereo Matching Algorithm with the Strategy of Population-based Incremental Learning," Journal of Information Processing Systems, vol. 5, no. 2, pp. 105-116, 2009. DOI: 10.3745/JIPS.2009.5.2.105.

[ACM Style]
Dong-Hu Nie, Kyu-Phil Han, and Heng-Suk Lee. 2009. GPU-based Stereo Matching Algorithm with the Strategy of Population-based Incremental Learning. Journal of Information Processing Systems, 5, 2, (2009), 105-116. DOI: 10.3745/JIPS.2009.5.2.105.