Comparative Analysis of Stereo-Matching Technologies for Emphasizing Stereo-Vision Applications
Abstract
Stereo vision is a growing research domain which seeks the attention of various researchers to attain deeper scene extraction. This work provides an extensive analysis towards the stereo-matching algorithms and stereo-vision to resolve the problems related to it. The analysis towards the stereo matching technologies is executed with benchmark standards with the focus on stereo vision methods. Thus the comparison of stereo matching algorithms can be done through the implementation of stereo vision application in a particular domain so that the results for the algorithms are comparatively analyzed. In most cases, the analysis and comparison are performed with statistical analysis and emphasize the benefits of various stereo algorithms. Some approaches give higher computational cost with expected outcomes over the lower time frame and provides competency towards parallel processing. The results obtained from the various stereo matching algorithms through the identified different parameters of bad pixels.