Varma, M. ; Ray, D. (2007) Learning The Discriminative Power-Invariance Trade-Off In: Proceedings of the IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil.
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Abstract
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visual similarity. Looking past initial differences, what really distinguishes one descriptor from another is the trade�off that it achieves between discriminative power and invariance. Since this trade-off must vary from task to task, no single descriptor can be optimal in all situations.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to IEEE International Conference on Computer Vision. |
| ID Code: | 119703 |
| Deposited On: | 16 Jun 2021 09:53 |
| Last Modified: | 16 Jun 2021 09:53 |
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