Research Projects
| 1. SLIC | 2. Ambiguity Reduction | 3. Localized Semantics |
| 4. Continuous DTW | 5. NNI | 6. Emotion Modeling |
3. Evaluation of Localized Semantics In Images
In this project, we create a new data set of 1014 images with manual segmentations and semantic labels for each segment, and present a methodology for using this kind of data for recognition evaluation. The evaluation methodology establishes protocols for mapping machine segmentation to human segmentation, scoring matches at different levels of specificity, and taking synonyms, sense ambiguity and multiple labels into accounted. Based on these protocols, we develop two evaluation approaches for measuring the range and the frequency of semantics that an algorithm can recognize correctly.More details such as data and software can be found on the project webpage.
Related Publications
- 1. K. Barnard, Q. Fan, R. Swaminathan, A. Hoogs, R. Collins, P. Rondot and J. Kaufhold, Evaluation of localized semantics: Data, methodology, and experiments, International Journal of Computer Vision (IJCV) (to appear). [pdf]