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Pedro Miraldo
Mitsubishi Electric Research Labs
201 Broadway, Cambridge, MA
miraldo (at) merl (dot) com
I am a Senior Principal Research Scientist at MERL Mitsubishi Electric Research Laboratories. Before joining MERL, I was a second-stage Researcher (comparable to an Assistant Research Professor) at the Institute for Systems & Robotics and the Department of Electrical & Computer Engineering, IST Instituto Superior Técnico, Lisboa. From 2018 to 2019, I was a postdoctoral associate at KTH Royal Institute of Technology. Previously, I held an FCT postdoctoral researcher grant (a highly competitive individual research grant) at IST.
I received my Master's and Ph.D. degrees in Electrical and Computer Engineering from the Faculty of Sciences and Technology, University of Coimbra, Portugal.
My main research topics are 3D computer vision, robot vision, and active vision.
News:
- Paper accepted to the Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
- Paper accepted to the IEEE/CVF International Conference on Computer Vision (ICCV), 2025 as Highlight.
- Paper accepted to the International Conference on 3D Vision (3DV), 2025.
- Paper accepted to the IEEE Robotics and Automation Letters (RA-L), 2024.
- Paper accepted to the European Conference on Computer Vision (ECCV), 2024.
- Paper accepted to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 as Highlight.
Selected Projects and Publications:
-
Fast and Accurate 3D Registration from Line Intersection Constraints, from
A. Mateus, S. Ranade, S. Ramalingam, and P. Miraldo,
International Journal Computer Vision (IJCV), 2023. [doi, code] -
Minimal Solvers for 3D Scan Alignment with Pairs of Intersecting Lines, from
A. Mateus, S. Ramalingam, and P. Miraldo,
IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), 2020. [cfv, doi, video, code] -
Mapping of Sparse 3D Data using Alternating Projection, from
S. Ranade, X. Yu, S. Kakkar, P. Miraldo, and S. Ramalingam,
Asian Conf. Computer Vision (ACCV), 2020. [arXiv, video, doi]
-
A Unified Model for Line Projections in Catadioptric Cameras with Rotationally Symmetric Mirrors,
from
P. Miraldo and Jose Pedro Iglesias
IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), 2022. [pdf,doi,code] -
Analytical Modeling of Vanishing Points and Curves in Catadioptric Cameras, from
Pedro Miraldo, Francisco Eiras, and Srikumar Ramalingam
IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), 2020. [arXiv:1804.09460,doi];
-
An observer cascade for velocity and multiple line estimation, from
A. Mateus, P. U. Lima, and P. Miraldo,
IEEE Int'l Conf. Robotics and Automation (ICRA), 2022. [arXiv, doi] -
On Incremental Structure-from-Motion using Lines, from
A. Mateus, O. Tahri, A. P. Aguiar, P. U. Lima, and P. Miraldo,
Transactions on Robotics (T-RO), 2021. [arXiv, doi] -
Active Estimation of 3D Lines in Spherical Coordinates, from
A. Mateus, O. Tahri, and P. Miraldo,
American Control Conference (ACC), 2019. [arXiv, doi] -
Active Structure-from-Motion for 3D Straight Lines, from
A. Mateus, O. Tahri, and P. Miraldo,
IEEE/RSJ Int'l Conf. Intelligent Robots and Systems (IROS), 2018. [link, video, doi]
-
On the Generalized Essential Matrix Correction: An efficient solution to the problem and its
applications, from
Pedro Miraldo and Joao R. Cardoso (2020),
Journal of Mathematical Imaging and Vision (JMIV). [arXiv:1709.06328, doi] -
Generalized Essential Matrix: Properties of the Singular Value Decomposition, from
P. Miraldo and H. Araujo (2015),
Image and Vision Computing (IVC). [pdf, doi]
-
A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and Lines,
from
P. Miraldo, T. Dias, S. Ramalingam,
European Conf. Computer Vision (ECCV), 2018. [link,project,video] -
Pose Estimation for General Cameras using Lines, from
P. Miraldo, H. Araujo and N. Gonçalves,
IEEE Trans. Cybermetic (Systems, Man, and Cybernetics, Part B), 2015. [pdf, doi, video] -
Planar Pose Estimation for General Cameras using Known 3D Lines, from
P. Miraldo and H. Araujo,
IEEE/RSJ Int'l Conf. Intelligent Robots and Systems (IROS), 2014. [pdf, doi, video]
-
Calibration of Smooth Camera Models, from
P. Miraldo and H. Araujo (2013),
IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI). [pdf, appendix, doi] -
Point-based Calibration Using a Parametric Representation of General Imaging Models,
from
P. Miraldo, H. Araujo, and J. Queiro (2011),
IEEE Int'l Conf. Computer Vision (ICCV). [pdf, appendix, doi]
Last updated: Oct 20, 2025
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