Hierarchical Scene Annotation
Abstract
We present a computer-assisted annotation system, together with a labeled dataset and benchmark suite, for evaluating an algorithm's ability to recover hierarchical scene structure. We evolve segmentation groundtruth from the two-dimensional image partition into a tree model that captures both occlusion and object-part relationships among possibly overlapping regions. Our tree model extends the segmentation problem to encompass object detection, object-part containment, and figure-ground ordering. We mitigate the cost of providing richer groundtruth labeling through a new web-based annotation tool with an intuitive graphical interface for rearranging the region hierarchy. Using precomputed superpixels, our tool also guides creation of user-specified regions with pixel-perfect boundaries. Widespread adoption of this human-machine combination should make the inaccuracies of bounding box labeling a relic of the past. Evaluating the state-of-the-art in fully automatic image segmentation reveals that it produces accurate two-dimension partitions, but does not respect groundtruth object-part structure. Our dataset and benchmark is the first to quantify these inadequacies. We illuminate recovery of rich scene structure as an important new goal for segmentation.
Additional Information
© 2013. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. ONR MURI N00014-10-1-0933 and ARO/JPL-NASA Stennis NAS7.03001 supported this work. Part of Stella Yu's work was supported by NSF CAREER IIS-1257700. Thanks to Alex Jose and Piotr Dollar for helpful discussion on user interfaces for segmentationAttached Files
Published - paper0084.pdf
Files
Name | Size | Download all |
---|---|---|
md5:59d061eb05d5d24a8e90cac376ec4f87
|
9.8 MB | Preview Download |
Additional details
- Eprint ID
- 94260
- Resolver ID
- CaltechAUTHORS:20190328-154052779
- N00014-10-1-0933
- Office of Naval Research (ONR)
- NAS7.03001
- NASA
- Army Research Office (ARO)
- IIS-1257700
- NSF
- Created
-
2019-03-28Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field