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Sample and Pixel Weighting Strategies for Robust Incremental Visual Tracking

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Localized model order reduction and domain decomposition methods for coupled heterogeneous systems

Jan Sickmann Hesthaven, Niccolo' Discacciati

We propose a model order reduction technique to accurately approximate the behavior of multi-component systems without any a-priori knowledge of the coupled model. In the offline phase, we construct independent surrogate models by solving the local problem ...

WILEY2023

Autonomous illumination control for localization microscopy

Suliana Manley, Kyle Michael Douglass, Baptiste Romain Samuel Ottino, Marcel Stefko

Super-resolution fluorescence microscopy improves spatial resolution, but this comes at a loss of image throughput and presents unique challenges in identifying optimal acquisition parameters. Microscope automation routines can offset these drawbacks, but ...

OPTICAL SOC AMER2018

Real-Time Generative Hand Modeling and Tracking

Anastasia Tkach

In our everyday life we interact with the surrounding environment using our hands. A main focus of recent research has been to bring such interaction to virtual objects, such as the ones projected in virtual reality devices, or super-imposed as holograms i ...

EPFL2018

Sphere-Meshes for Real-Time Hand Modeling and Tracking

Mark Pauly, Andrea Tagliasacchi, Anastasia Tkach

Modern systems for real-time hand tracking rely on a combination of discriminative and generative approaches to robustly recover hand poses. Generative approaches require the specification of a geometric model. In this paper, we propose a the use of sphere ...

Assoc Computing Machinery2016

Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications

Abdulkadir Akin

Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and tracking, computer games, 3D television, and free view-point synthesis. These applications r ...

EPFL2015

Tracking Interacting Objects in Image Sequences

Xinchao Wang

Object tracking in image sequences is a key challenge in computer vision. Its goal is to follow objects that move or evolve over time while preserving the identity of each object. However, most existing approaches focus on one class of objects and model on ...

EPFL2015

2-Point-based Outlier Rejection for Camera-IMU Systems with applications to Micro Aerial Vehicles

Davide Scaramuzza

This paper presents a novel method to perform the outlier rejection task between two different views of a camera rigidly attached to an Inertial Measurement Unit (IMU). Only two feature correspondences and gyroscopic data from IMU measurerments are used to ...

2014

Object Classification and Detection in High Dimensional Feature Space

Charles Dubout

Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...

Programme doctoral en Informatique, Communications et Information2013

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Pascal Frossard, Zafer Arican

We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...

Institute of Electrical and Electronics Engineers2012

Learning to Detect Objects with Minimal Supervision

Karim Ali

Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...

EPFL2012