Euclidean reconstruction from image sequences with varying and unknown focal length and principal point A Heyden, K Astrom Proceedings of IEEE Computer Society Conference on Computer Vision and …, 1997 | 354 | 1997 |
Euclidean reconstruction from constant intrinsic parameters A Heyden, K Astrom proceedings of 13th International Conference on Pattern Recognition 1, 339-343, 1996 | 293 | 1996 |
Three‐dimensional biofilm model with individual cells and continuum EPS matrix E Alpkvist, C Picioreanu, MCM Van Loosdrecht, A Heyden Biotechnology and bioengineering 94 (5), 961-979, 2006 | 278 | 2006 |
An iterative factorization method for projective structure and motion from image sequences A Heyden, R Berthilsson, G Sparr Image and Vision Computing 17 (13), 981-991, 1999 | 184 | 1999 |
Feature-free registration of dissimilar images using a robust similarity metric M Pettersson, A Rosenqvist, A Heyden, M Almers US Patent 6,268,611, 2001 | 157 | 2001 |
Reconstruction from image sequences by means of relative depths A Heyden International journal of computer vision 24 (2), 155-161, 1997 | 106 | 1997 |
Minimal conditions on intrinsic parameters for euclidean reconstruction A Heyden, K Åkström Asian Conference on Computer Vision, 169-176, 1998 | 101 | 1998 |
Flexible calibration: Minimal cases for auto-calibration A Heyden, K Astrom Proceedings of the Seventh IEEE International Conference on Computer Vision …, 1999 | 89 | 1999 |
Algebraic properties of multilinear constraints A Heyden, K Åström Mathematical Methods in the Applied Sciences 20 (13), 1135-1162, 1997 | 89 | 1997 |
Towards grading gleason score using generically trained deep convolutional neural networks H Källén, J Molin, A Heyden, C Lundström, K Åström 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1163-1167, 2016 | 88 | 2016 |
Projective structure and motion from image sequences using subspace methods A Heyden Proceedings of the Scandinavian Conference on Image Analysis 2, 963-968, 1997 | 86 | 1997 |
Geometry and algebra of multiple projective transformations A Heyden Lund Institute of Technology, Department of Mathematics, 1995 | 85 | 1995 |
A common framework for multiple view tensors A Heyden Computer Vision—ECCV'98: 5th European Conference on Computer Vision …, 1998 | 84 | 1998 |
Using conic correspondences in two images to estimate the epipolar geometry F Kahl, A Heyden Sixth International Conference on Computer Vision (IEEE Cat. No. 98CH36271 …, 1998 | 80 | 1998 |
Multiple view geometry A Heyden, M Pollefeys Emerging topics in computer vision 3, 45-108, 2005 | 77 | 2005 |
A fast algorithm for level set-like active contours B Nilsson, A Heyden Pattern Recognition Letters 24 (9-10), 1331-1337, 2003 | 69 | 2003 |
Affine structure and motion from points, lines and conics F Kahl, A Heyden International Journal of Computer Vision 33, 163-180, 1999 | 67 | 1999 |
Covariance propagation and next best view planning for 3d reconstruction S Haner, A Heyden Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 64 | 2012 |
Degenerate cases and closed-form solutions for camera calibration with one-dimensional objects P Hammarstedt, P Sturm, A Heyden Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 1 …, 2005 | 61 | 2005 |
Segmentation of complex cell clusters in microscopic images: Application to bone marrow samples B Nilsson, A Heyden Cytometry Part A: The Journal of the International Society for Analytical …, 2005 | 54 | 2005 |