ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture

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This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

We present DepthInSpace, a self-supervised deep-learning method for depth estimation using a structured-light camera. The design of this method is motivated by the commercial use case of embedded depth sensors in nowadays smartphones. We first propose to u ...

One of the main challenges in underwater robot localization is the scarcity of external positioning references. Therefore, accurate inertial localization in between external position updates is crucial for applications such as underwater environmental samp ...

This study aimed to introduce and validate a new method to estimate and correct the orientation drift measured from foot-worn inertial sensors. A modified strap-down integration (MSDI) was proposed to decrease the orientation drift, which, in turn, was fur ...

In this paper we propose an unsupervised feature extraction method to capture temporal information on monocular videos, where we detect and encode subject of interest in each frame and leverage contrastive self-supervised (CSS) learning to extract rich lat ...

Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed. The main drawback of these ...

Small unmanned aerial vehicles (UAV) have penetrated multiple domains over the past years. In GNSS-denied or indoor environments, aerial robots require a robust and stable localization system, often with external feedback, in order to fly safely. Motion ca ...

Bluetooth Low Energy (BLE) has become very common for tracking applications in homes, stadiums, malls, and hospitals over the last decade. With the outbreak of COVID, the technology was widely used for local tracking of the virus spread [1]. However, despi ...

Supervised and unsupervised kernel-based algorithms widely used in the physical sciences depend upon the notion of similarity. Their reliance on pre-defined distance metrics-e.g. the Euclidean or Manhattan distance-are problematic especially when used in c ...

We propose a novel controller for powered prosthetic arms, where fused EMG and gaze data predict the desired end-point for a full arm prosthesis, which could drive the forward motion of individual joints. We recorded EMG, gaze, and motion-tracking during p ...

ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture

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Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Model-based 3D Face Reconstruction

Discrete-Choice Mining of Social Processes

Supervised learning and inference of spiking neural networks with temporal coding

Automated Human Motion Analysis and Synthesis

DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation

Online Kinematic and Dynamic Parameter Estimation for Autonomous Surface and Underwater Vehicles

Drift-Free Foot Orientation Estimation in Running Using Wearable IMU

Temporal Representation Learning on Monocular Videos for 3D Human Pose Estimation

Learning stereo reconstruction with deep neural networks

UWB-based system for UAV Localization in GNSS-Denied Environments: Characterization and Dataset

New Design of Antenna Array for Bluetooth Direction Finding

Metric learning for kernel ridge regression: assessment of molecular similarity

Intent Prediction Based on Biomechanical Coordination of EMG and Vision-Filtered Gaze for End-Point Control of an Arm Prosthesis