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Conference Paper: A Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors
| Title | A Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors |
|---|---|
| Authors | |
| Issue Date | 2002 |
| Citation | Symposium for Pattern Recognition DAGM02, Zurich, Switzerland, 2002. In Van Gool, L (Ed.). Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, v. 2449, p. 387-394. Berlin, Heidelberg: Springer, 2002 How to Cite? |
| Abstract | In this paper, we consider the problem of projective reconstruction based on the factorization method. Unlike existing factorization based methods which minimize the SVD reprojection error, we propose to estimate the projective depths by minimizing the 2-D reprojection errors. An iterative algorithm is developed to minimize 2-D reprojection errors. This algorithm reconstructs the projective depths robustly and does not rely on any geometric knowledge, such as epipolar geometry. Simulation results using synthetic data are given to illustrate the performance of the algorithm. |
| Persistent Identifier | http://hdl.handle.net/10722/99607 |
| ISBN | |
| ISSN | 2023 SCImago Journal Rankings: 0.606 |
| Series/Report no. | Lecture Notes in Computer Science book series |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Tang, AWK | en_HK |
| dc.contributor.author | Hung, YS | en_HK |
| dc.date.accessioned | 2010-09-25T18:37:12Z | - |
| dc.date.available | 2010-09-25T18:37:12Z | - |
| dc.date.issued | 2002 | en_HK |
| dc.identifier.citation | Symposium for Pattern Recognition DAGM02, Zurich, Switzerland, 2002. In Van Gool, L (Ed.). Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, v. 2449, p. 387-394. Berlin, Heidelberg: Springer, 2002 | - |
| dc.identifier.isbn | 978-3-540-44209-7 | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/99607 | - |
| dc.description.abstract | In this paper, we consider the problem of projective reconstruction based on the factorization method. Unlike existing factorization based methods which minimize the SVD reprojection error, we propose to estimate the projective depths by minimizing the 2-D reprojection errors. An iterative algorithm is developed to minimize 2-D reprojection errors. This algorithm reconstructs the projective depths robustly and does not rely on any geometric knowledge, such as epipolar geometry. Simulation results using synthetic data are given to illustrate the performance of the algorithm. | - |
| dc.language | eng | en_HK |
| dc.relation.ispartof | Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science | en_HK |
| dc.relation.ispartofseries | Lecture Notes in Computer Science book series | - |
| dc.title | A Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors | en_HK |
| dc.type | Conference_Paper | en_HK |
| dc.identifier.email | Tang, AWK: wktang@hku.hk | en_HK |
| dc.identifier.email | Hung, YS: yshung@eee.hku.hk | en_HK |
| dc.identifier.authority | Hung, YS=rp00220 | en_HK |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1007/3-540-45783-6_47 | - |
| dc.identifier.scopus | eid_2-s2.0-34547338771 | - |
| dc.identifier.hkuros | 82485 | en_HK |
| dc.identifier.issnl | 0302-9743 | - |