Concept

Camera matrix

Related publications (19)

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Laurent Valentin Jospin, Jesse Ray Murray Lahaye

Bayesian statistics is concerned with the integration of new information obtained through observations with prior knowledge, and accordingly, is often related to information theory (Jospin 2022). Recursive Bayesian estimation methods, such as Kalman Filter ...

2023

Using Animal Motion Capture to Learn Neural Representations

Semih Günel

Understanding behavior from neural activity is a fundamental goal in neuroscience. It has practical applications in building robust brain-machine interfaces, human-computer interaction, and assisting patients with neurological disabilities. Despite the eve ...

EPFL2022

Multi-View Triangulation: Systematic Comparison and an Improved Method

Peng Song

Triangulation is an important task in the 3D reconstruction of computer vision. It seems simple to find the position of a point in 3D space when its 2D perspective projections in multi-view images are given and the corresponding camera projection matrices ...

2020

Accurate Nod and 3D Gaze Estimation for Social Interaction Analysis

Yu Yu

Non-verbal behaviours play an important role in human communication since it can indicate human attention, serve as communication cue in interactions, or even reveal higher level personal constructs. For instance, head nod, a common non-verbal behaviour, c ...

EPFL2020

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Pascal Fua, Mathieu Salzmann, Agata Justyna Mosinska, Mateusz Kozinski

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation giv ...

ELSEVIER2020

Gravity as a Reference for Estimating a Person's Height from Video

Pascal Fua, Helge Jochen Rhodin, Semih Günel, Didier Bieler

Estimating the metric height of a person from monocular imagery without additional assumptions is ill-posed. Existing solutions either require manual calibration of ground plane and camera geometry, special cameras, or reference objects of known size. We f ...

IEEE2019

Performance assessment of integrated sensor orientation with a low-cost GNSS receiver

Jan Skaloud, Martin Rehak

Mapping with Micro Aerial Vehicles (MAVs whose weight does not exceed 5 kg) is gaining importance in applications such as corridor mapping, road and pipeline inspections, or mapping of large areas with homogeneous surface structure, e.g. forest or agricult ...

Copernicus GmbH2017

Head Nod Detection from a Full 3D Model

Jean-Marc Odobez, Yu Yu, Yiqiang Chen

As a non-verbal communication mean, head gestures play an important role in face-to-face conversation and recognizing them is therefore of high value for social behavior analysis or Human Robotic Interactions (HRI) modelling. Among the various gestures, he ...

2015

Integration of dynamic vision sensor with inertial measurement unit for electronically stabilized event-based vision

Neuromorphic spike event-based dynamic vision sensors (DVS) offer the possibility of fast, computationally efficient visual processing for navigation in mobile robotics. To extract motion parallax cues relating to 3D scene structure, the uninformative came ...

IEEE2014

Light ﬁeld panorama by a plenoptic camera

Martin Vetterli, Paolo Prandoni, Loïc Arnaud Baboulaz, Zhou Xue

Consumer-grade plenoptic camera Lytro draws a lot of interest from both academic and industrial world. However its low resolution in both spatial and angular domain prevents it from being used for ﬁne and detailed light ﬁeld acquisition. This paper propose ...

SPIE2013

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.