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Author  |
Naveen Onkarappa; Angel Sappa | ||||
| Title | Laplacian Derivative based Regularization for Optical Flow Estimation in Driving Scenario | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 8048 | Issue | Pages | 483-490 | |
| Keywords | Optical flow; regularization; Driver Assistance Systems; Performance Evaluation | ||||
| Abstract | Existing state of the art optical flow approaches, which are evaluated on standard datasets such as Middlebury, not necessarily have a similar performance when evaluated on driving scenarios. This drop on performance is due to several challenges arising on real scenarios during driving. Towards this direction, in this paper, we propose a modification to the regularization term in a variational optical flow formulation, that notably improves the results, specially in driving scenarios. The proposed modification consists on using the Laplacian derivatives of flow components in the regularization term instead of gradients of flow components. We show the improvements in results on a standard real image sequences dataset (KITTI). | ||||
| Address | York; UK; August 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-40245-6 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | ADAS; 600.055; 601.215 | Approved | no | ||
| Call Number | Admin @ si @ OnS2013b | Serial | 2244 | ||
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