Investigating the performance of Correspondence Algorithms in Vision based Driver-assistance in Indoor Environment

This paper presents the experimental comparison of fourteen stereo matching algorithms in variant illumination conditions. Different adaptations of global and local stereo matching techniques are chosen for evaluation The variant strength and weakness of the chosen correspondence algorithms are explored by employing the methodology of the prediction error strategy. The algorithms are gauged on the basis of their performance on real world data set taken in various indoor lighting conditions and at different times of the day

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