In this paper, we exploit the analogy between protein sequence alignment and image pair correspondence to design a bioinformatics-inspired framework for stereo matching based on dynamic programming. This approach also led to the creation of a meaningfulness graph, which helps to predict matching validity according to image overlap and pixel similarity. Finally, we propose an automatic procedure to estimate automatically all matching parameters. This work is evaluated qualitatively and quantitatively using a standard benchmarking dataset and by conducting stereo matching experiments between images captured at different resolutions. Results confirm the validity of the computer vision/bioinformatics analogy to develop a versatile and accurate low complexity stereo matching algorithm.
|Title of host publication||VISAPP 2011 - Proceedings of the International Conference on Computer Vision Theory and Application|
|Number of pages||9|
|Publication status||Published - 01 Jan 2011|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition