Global optimal searching for textureless 3D object tracking
| LEADER | caa a22 4500 | ||
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| 001 | 605540918 | ||
| 003 | CHVBK | ||
| 005 | 20210128100913.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150601xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00371-015-1098-7 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00371-015-1098-7 | ||
| 245 | 0 | 0 | |a Global optimal searching for textureless 3D object tracking |h [Elektronische Daten] |c [Guofeng Wang, Bin Wang, Fan Zhong, Xueying Qin, Baoquan Chen] |
| 520 | 3 | |a Textureless 3D object tracking of the object's position and orientation is a considerably challenging problem, for which a 3D model is commonly used. The 3D-2D correspondence between a known 3D object model and 2D scene edges in an image is standardly used to locate the 3D object, one of the most important problems in model-based 3D object tracking. State-of-the-art methods solve this problem by searching correspondences independently. However, this often fails in highly cluttered backgrounds, owing to the presence of numerous local minima. To overcome this problem, we propose a new method based on global optimization for searching these correspondences. With our search mechanism, a graph model based on an energy function is used to establish the relationship of the candidate correspondences. Then, the optimal correspondences can be efficiently searched with dynamic programming. Qualitative and quantitative experimental results demonstrate that the proposed method performs favorably compared to the state-of-the-art methods in highly cluttered backgrounds. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2015 | ||
| 690 | 7 | |a 3D tracking |2 nationallicence | |
| 690 | 7 | |a 3D-2D correspondence |2 nationallicence | |
| 690 | 7 | |a Global optimization |2 nationallicence | |
| 690 | 7 | |a Dynamic programming |2 nationallicence | |
| 700 | 1 | |a Wang |D Guofeng |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | |
| 700 | 1 | |a Wang |D Bin |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | |
| 700 | 1 | |a Zhong |D Fan |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | |
| 700 | 1 | |a Qin |D Xueying |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | |
| 700 | 1 | |a Chen |D Baoquan |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | |
| 773 | 0 | |t The Visual Computer |d Springer Berlin Heidelberg |g 31/6-8(2015-06-01), 979-988 |x 0178-2789 |q 31:6-8<979 |1 2015 |2 31 |o 371 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00371-015-1098-7 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00371-015-1098-7 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wang |D Guofeng |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wang |D Bin |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Zhong |D Fan |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Qin |D Xueying |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Chen |D Baoquan |u School of Computer Science and Technology, Shandong University, Jinan, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t The Visual Computer |d Springer Berlin Heidelberg |g 31/6-8(2015-06-01), 979-988 |x 0178-2789 |q 31:6-8<979 |1 2015 |2 31 |o 371 | ||