Performance characteristics of vision algorithms
Machine Vision and Applications - Special issue on performance evaluation
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Physically Based Rendering: From Theory to Implementation
Physically Based Rendering: From Theory to Implementation
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pruning SIFT for scalable near-duplicate image matching
ADC '07 Proceedings of the eighteenth conference on Australasian database - Volume 63
Stereo Processing by Semiglobal Matching and Mutual Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance characterization in computer vision: A guide to best practices
Computer Vision and Image Understanding
Evaluation of Stereo Matching Costs on Images with Radiometric Differences
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Third Eye for Performance Evaluation in Stereo Sequence Analysis
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Stereo by two-level dynamic programming
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Ground truth evaluation of stereo algorithms for real world applications
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Illumination invariant cost functions in semi-global matching
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Real-World stereo-analysis evaluation
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
On performance analysis of optical flow algorithms
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
| Hi-index | 0.00 |
Current research in stereo image analysis focuses on improving matching algorithms in terms of accuracy, computational costs, and robustness towards real-time applicability for complex image data and 3D scenes. Interestingly, performance testing takes place for a huge number of algorithms, but, typically, on very small sets of image data only. Even worse, there is little reasoning whether data as commonly applied is actually suitable to prove robustness or even correctness of a particular algorithm. We argue for the need of testing stereo algorithms on a much broader variety of image data then done so far by proposing a simple measure for putting image stereo data of different quality into relation to each other. Potential applications include purpose-directed decisions for the selection of image stereo data for testing the applicability of matching techniques under particular situations, or for realtime estimation of stereo performance (without any need for providing ground truth) in cases where techniques should be selected depending on the given situation.