caa a22 4500 605540918 CHVBK 20210128100913.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00371-015-1098-7 doi (NATIONALLICENCE)springer-10.1007/s00371-015-1098-7 Global optimal searching for textureless 3D object tracking [Elektronische Daten] [Guofeng Wang, Bin Wang, Fan Zhong, Xueying Qin, Baoquan Chen] 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. Springer-Verlag Berlin Heidelberg, 2015 3D tracking nationallicence 3D-2D correspondence nationallicence Global optimization nationallicence Dynamic programming nationallicence Wang Guofeng School of Computer Science and Technology, Shandong University, Jinan, China aut Wang Bin School of Computer Science and Technology, Shandong University, Jinan, China aut Zhong Fan School of Computer Science and Technology, Shandong University, Jinan, China aut Qin Xueying School of Computer Science and Technology, Shandong University, Jinan, China aut Chen Baoquan School of Computer Science and Technology, Shandong University, Jinan, China aut The Visual Computer Springer Berlin Heidelberg 31/6-8(2015-06-01), 979-988 0178-2789 31:6-8<979 2015 31 371 https://doi.org/10.1007/s00371-015-1098-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-015-1098-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Guofeng School of Computer Science and Technology, Shandong University, Jinan, China aut NATIONALLICENCE 700 1- Wang Bin School of Computer Science and Technology, Shandong University, Jinan, China aut NATIONALLICENCE 700 1- Zhong Fan School of Computer Science and Technology, Shandong University, Jinan, China aut NATIONALLICENCE 700 1- Qin Xueying School of Computer Science and Technology, Shandong University, Jinan, China aut NATIONALLICENCE 700 1- Chen Baoquan School of Computer Science and Technology, Shandong University, Jinan, China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/6-8(2015-06-01), 979-988 0178-2789 31:6-8<979 2015 31 371