Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality
- Resource Type
- Conference
- Authors
- Marquez-Valle, Patricia; Gil, Debora; Hernandez-Sabate, Aura
- Source
- 2013 IEEE International Conference on Computer Vision Workshops Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on. :624-631 Dec, 2013
- Subject
- Computing and Processing
Measurement uncertainty
Adaptive optics
Optical imaging
Upper bound
Integrated optics
Probabilistic logic
Computer vision
Optical flow
confidence measures
performance evaluation
- Language
Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.