This paper outlines existing matching diagnostics, which may be used for identifying invalid matches and estimating the probability of a correct match. In addition, it proposes a new diagnostic for error prediction which can be used with the rank and census transforms. Both the existing and the new diagnostics have been evaluated and compared for a number of test images. In each case, a confidence estimate was computed for every location of the disparity map, and disparities having a low confidence estimate removed from the disparity map. Collectively, these confidence estimates may be termed a confidence map. Such information would be useful for potential applications of stereo vision such as automation and navigation
In this study, we integrate confidence into efficient large-scale stereo (ELAS) matching to produce ...
More results for all dataset for Disparity Selective Stereo Matching Using Correlation Confidence Me...
International audienceWhile machine learning has been instrumental to the ongoing progress in most a...
This paper outlines existing matching diagnostics, which may be used for identifying invalid matches...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
In this paper we propose an approach for estimating the confidence of stereo matches for superpixel-...
none8siStereo matching is one of the most popular techniques to estimate dense depth maps by finding...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
Confidence measures estimate unreliable disparity assignments performed by a stereo matching algorit...
We propose a new approach to associate supervised learning-based confidence prediction with the ster...
The rank transform is a nonparametric technique which has been recently proposed for the stereo matc...
Stereo vision is a popular technique to infer depth from two or more images. In this field, confiden...
One of the inherent problems with stereo disparity estimation algorithms is the lack of reliability ...
Confidence measures for stereo earned increasing popularity in most recent works concerning stereo,...
In this study, we integrate confidence into efficient large-scale stereo (ELAS) matching to produce ...
More results for all dataset for Disparity Selective Stereo Matching Using Correlation Confidence Me...
International audienceWhile machine learning has been instrumental to the ongoing progress in most a...
This paper outlines existing matching diagnostics, which may be used for identifying invalid matches...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
In this paper we propose an approach for estimating the confidence of stereo matches for superpixel-...
none8siStereo matching is one of the most popular techniques to estimate dense depth maps by finding...
The authors present a qualitative and quantitative comparison of various similarity measures that fo...
Confidence measures estimate unreliable disparity assignments performed by a stereo matching algorit...
We propose a new approach to associate supervised learning-based confidence prediction with the ster...
The rank transform is a nonparametric technique which has been recently proposed for the stereo matc...
Stereo vision is a popular technique to infer depth from two or more images. In this field, confiden...
One of the inherent problems with stereo disparity estimation algorithms is the lack of reliability ...
Confidence measures for stereo earned increasing popularity in most recent works concerning stereo,...
In this study, we integrate confidence into efficient large-scale stereo (ELAS) matching to produce ...
More results for all dataset for Disparity Selective Stereo Matching Using Correlation Confidence Me...
International audienceWhile machine learning has been instrumental to the ongoing progress in most a...