Hou, Xiaodi and Yuille, Alan and Koch, Christof (2012) A Meta-Theory of Boundary Detection Benchmarks. In: NIPS 2012 Workshop on Human Computation for Science and Computational Sustainability, 3-6 December 2012, Lake Tahoe, Nevada. http://resolver.caltech.edu/CaltechAUTHORS:20130816-103412043
- Submitted Version
See Usage Policy.
Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:20130816-103412043
Human labeled datasets, along with their corresponding evaluation algorithms, play an important role in boundary detection. We here present a psychophysical experiment that addresses the reliability of such benchmarks. To find better remedies to evaluate the performance of any boundary detection algorithm, we propose a computational framework to remove inappropriate human labels and estimate the instrinsic properties of boundaries.
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||The first author would like to thank Liwei Wang, Yin Li, Xi (Stephen) Chen, and Katrina Ligett. The research was supported by the ONR via an award made through Johns Hopkins University and by the Mathers Foundation.|
|Group:||Koch Laboratory, KLAB|
|Subject Keywords:||Computer Vision and Pattern Recognition|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||KLAB Import|
|Deposited On:||04 Mar 2013 22:34|
|Last Modified:||27 Aug 2013 23:26|
Repository Staff Only: item control page