activity
20202025
most citedFrom noisy point clouds to complete ear shapes: unsupervised pipeline

2 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

math.ST2025★ 1 cited

A Proof of Strong Consistency of Maximum Likelihood Estimator for Independent Non-Identically Distributed Data

Ricardo Ferreira, Filipa Valdeira, Marta Guimarães +1

We give a general proof of the strong consistency of the Maximum Likelihood Estimator for the case of independent non-identically distributed (i.n.i.d) data, assuming that the dens…

eess.SY2024

Satellite Safe Margin: Fast solutions for Conjunction Analysis

Ricardo N. Ferreira, Marta Guimarães, Cláudia Soares

The amount of debris in orbit has increased significantly over the years. With the recent growth of interest in space exploration, conjunction assessment has become a central issue…

math.OC2024

Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low-Earth Orbit

Ricardo Ferreira, Filipa Valdeira, Marta Guimarães +1

With the increase in the number of active satellites and space debris in orbit, the problem of initial orbit determination (IOD) becomes increasingly important, demanding a high ac…

eess.SY2023

One-Shot Initial Orbit Determination in Low-Earth Orbit

Ricardo Ferreira, Marta Guimarães, Filipa Valdeira +1

Due to the importance of satellites for society and the exponential increase in the number of objects in orbit, it is important to accurately determine the state (e.g., position an…

astro-ph.EP2023

Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds

Ricardo Ferreira, Cláudia Soares, Marta Guimarães

The proliferation of space debris in LEO has become a major concern for the space industry. With the growing interest in space exploration, the prediction of potential collisions b…

cs.CV2022

Probabilistic Registration for Gaussian Process 3D shape modelling in the presence of extensive missing data

Filipa Valdeira, Ricardo Ferreira, Alessandra Micheletti +1

We propose a shape fitting/registration method based on a Gaussian Processes formulation, suitable for shapes with extensive regions of missing data. Gaussian Processes are a prove…

cs.CV2020★ 2 cited

From noisy point clouds to complete ear shapes: unsupervised pipeline

Filipa Valdeira, Ricardo Ferreira, Alessandra Micheletti +1

Ears are a particularly difficult region of the human face to model, not only due to the non-rigid deformations existing between shapes but also to the challenges in processing the…