Computer Vision and Image Understanding
Multiple view geometry in computer vision
Multiple view geometry in computer vision
How Hard is 3-View Triangulation Really?
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Uncertainty Models in Quasiconvex Optimization for Geometric Reconstruction
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Image Noise Induced Errors in Camera Positioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Triangulation for points on lines
Image and Vision Computing
Camera Displacement via Constrained Minimization of the Algebraic Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast optimal algorithm for L2 triangulation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Fast optimal three view triangulation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
| Hi-index | 0.00 |
Multiple-view L"2 triangulation is a key problem in computer vision. This paper addresses the standard case where all image points are available, and the case where some image points are not available. In the latter case, it is supposed that the unknown image point belongs to a known region such as a line segment or an ellipse, as it happens for instance due to occlusions. For this problem we propose two methods based on linear matrix inequalities (LMIs). The first method, named TFML, exploits the fundamental matrix and is fast (the average computational time with two and three-views is 0.01 and 0.05s on Matlab) at the expense of possible conservatism, which however it is shown to occur rarely in practice, and which can be immediately detected. The second method, named TPML, exploits the projection matrix, is slower, but allows one to reduce the conservatism by using techniques for optimization over polynomials. Various examples with synthetic and real data illustrate the proposed strategy.