Publications by Christos Marios Christoudias

Domain Adaptation for Microscopy Imaging

Pascal Fua, Christos Marios Christoudias, Carlos Joaquin Becker

Electron and Light Microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While Machine Learning algorithms can be used to help ...

Institute of Electrical and Electronics Engineers2015

Learning Image Descriptors with Boosting

Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

We propose a novel and general framework to learn compact but highly discriminative floating-point and binary local feature descriptors. By leveraging the boosting-trick we first show how to efficiently train a compact floating-point descriptor that is ver ...

Institute of Electrical and Electronics Engineers2015

Real-time landing place assessment in man-made environments

Pascal Fua, Vincent Lepetit, Xiaolu Sun, Christos Marios Christoudias

We propose a novel approach to the real-time landing site detection and assessment in unconstrained man-made environments using passive sensors. Because this task must be performed in a few seconds or less, existing methods are often limited to simple loca ...

Springer Verlag2014

Boosting Binary Keypoint Descriptors

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

Binary keypoint descriptors provide an efficient alternative to their floating-point competitors as they enable faster processing while requiring less memory. In this paper, we propose a novel framework to learn an extremely compact binary descriptor we ca ...

2013

Non-Linear Domain Adaptation with Boosting

Pascal Fua, Christos Marios Christoudias, Carlos Joaquin Becker

A common assumption in machine vision is that the training and test samples are drawn from the same distribution. However, there are many problems when this assumption is grossly violated, as in bio-medical applications where different acquisitions can gen ...

2013

Learning Image Descriptors with the Boosting-Trick

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...

2012