Publications by Alireza Ghasemi

Single-Sensor Source Localization Using Electromagnetic Time Reversal and Deep Transfer Learning: Application to Lightning

Farhad Rachidi-Haeri, Marcos Rubinstein, Alireza Ghasemi, Mohammad Azadifar, Hamidreza Karami, Amirhossein Mostajabi

Electromagnetic Time Reversal (EMTR) has been used to locate different types of electromagnetic sources. We propose a novel technique based on the combination of EMTR and Machine Learning (ML) for source localization. We show for the first time that ML tec ...

Springer Nature2019

Bound and Conquer: Improving Triangulation by Enforcing Consistency

Martin Vetterli, Alireza Ghasemi, Adam James Scholefield

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction error decays quadratically as more cameras are added to the system. Furtherm ...

2019

Point and sensor estimation from images

Martin Vetterli, Alireza Ghasemi, Adam James Scholefield

System comprising at least one sensor configured to take a set of images from different viewpoints of a scene; a processor configured to identifying a point source represented in the images of a set of images; computing for each image of the set of images ...

2017

Bound and Conquer : Properties, Algorithms, and Applications of Multi-Camera Imaging

Alireza Ghasemi

Using more than one camera to capture a scene has a long history in photography and the imaging industry. Inspired by how the human eye operates, researchers and industrial companies have always tried to compensate for the 3-D information lost during the c ...

EPFL2017

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Martin Vetterli, Alireza Ghasemi, Adam James Scholefield

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear time-complexity and a squared reconstruction error that decreases at least qua ...

Ieee2016

On the Accuracy of Point Localisation in a Circular Camera-Array

Martin Vetterli, Alireza Ghasemi, Adam James Scholefield

Although many advances have been made in light-field and camera-array image processing, there is still a lack of thorough analysis of the localisation accuracy of different multi-camera systems. By considering the problem from a frame-quantisation perspect ...

2015

Method and apparatus for identifying local features

Martin Vetterli, Laurent Michel Rime, Alireza Ghasemi

A method of local feature identification, comprising the steps of: retrieving data representing a lightfield (101); forming an epipolar volume (V) from the retrieved data; applying a transform to epipolar planes retrieved from said epipolar volume, so as t ...

2014

Scale-invariant representation of light field images for object recognition and tracking

Martin Vetterli, Alireza Ghasemi

Achieving perfect scale-invariance is usually not possible using classical color image features. This is mostly because of the fact that a traditional image is a two-dimensional projection of the real world. In contrast, light field imaging makes available ...

International Society for Optics and Photonics2014

Detecting Planar Surface Using a Light-Field Camera with Application to Distinguishing Real Scenes From Printed Photos

Martin Vetterli, Alireza Ghasemi

We propose a novel approach for detecting printed photos from natural scenes using a light-field camera. Our approach exploits the extra information captured by a light-field camera and the multiple views of scene in order to infer a compact feature vector ...

Ieee2014

Computationally efficient background subtraction in the light field domain

Martin Vetterli, Mahdad Hosseini Kamal, Alireza Ghasemi

Since the invention of first camera, people have always thought of new ways to capture moments. With the advent of digital photography, not only imaging systems have progressed, but also technology provides new user experience. The recently introduced ligh ...

International Society for Optics and Photonics2014

LCAV-31: a dataset for light field object recognition

Martin Vetterli, Nelly Julie Afonso, Alireza Ghasemi

We present LCAV-31, a multi-view object recognition dataset designed specifically for benchmarking light field image analysis tasks. The principal distinctive factor of LCAV-31 compared to similar datasets is its design goals and availability of novel visu ...

International Society for Optics and Photonics2014