Realistic 3D human saccades generated by a 6-DOF biomimetic robotic eye under optimal control.

We recently developed a biomimetic robotic eye with six independent tendons, each controlled by their own rotatory motor, and with insertions on the eye ball that faithfully mimic the biomechanics of the human eye. We constructed an accurate physical computational model of this system, and learned to control its nonlinear dynamics by optimising a cost that penalised saccade inaccuracy, movement duration, and total energy expenditure of the motors. To speed up the calculations, the physical simulator was approximated by a recurrent neural network (NARX).

Effects of Multimodal Exercise With Augmented Reality on Cognition in Community-Dwelling Older Adults.

Objectives: This study aims to investigate the effects of an exercise intervention using multimodal exercise with augmented reality and multimodal exercise-only on cognitive function in older adults living in a community dwelling.

Design: Quasi-experimental research study.

Setting And Participants: In this control study, 78 participants were divided into 2 experimental groups (with sessions 3 times a week for 12 weeks) and a control group (CG).

Fingerprint Recognition in Forensic Scenarios.

Fingerprints are unique patterns used as biometric keys because they allow an individual to be unambiguously identified, making their application in the forensic field a common practice. The design of a system that can match the details of different images is still an open problem, especially when applied to large databases or, to real-time applications in forensic scenarios using mobile devices. Fingerprints collected at a crime scene are often manually processed to find those that are relevant to solving the crime.

Skeleton Tracking Solutions for a Low-Cost Stroke Rehabilitation Support System.

Computer systems based on motion assessment are promising solutions to support stroke survivors' autonomous rehabilitation exercises. In this regard, researchers keep trying to achieve engaging and low-cost solutions suitable mainly for home use. Aiming to achieve a system with a minimal technical setup, we compare Microsoft Kinect, OpenPose, and MediaPipe skeleton tracking approaches for upper extremity quality of movement assessment after stroke.

Design, development, and evaluation of an interactive personalized social robot to monitor and coach post-stroke rehabilitation exercises.

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge.

Event-based feature tracking in a visual inertial odometry framework.

Event cameras report pixel-wise brightness changes at high temporal resolutions, allowing for high speed tracking of features in visual inertial odometry (VIO) estimation, but require a paradigm shift, as common practices from the past decades using conventional cameras, such as feature detection and tracking, do not translate directly. One method for feature detection and tracking is the Eventbased Kanade-Lucas-Tomasi tracker (EKLT), an hybrid approach that combines frames with events to provide a high speed tracking of features. Despite the high temporal resolution of the events, the local nature of the registration of features imposes conservative limits to the camera motion speed.

Acute Effects of Augmented Reality Exergames versus Cycle Ergometer on Reaction Time, Visual Attention, and Verbal Fluency in Community Older Adults.

Background: This study aims to investigate the acute effects of an augmented reality session and a cycle ergometer session compared to no exercise on the reaction times, cognitive flexibility, and verbal fluency of older adults.

Methods: Each participant did a familiarization with cognitive tests and the following three sessions: cycle ergometer, no exercise (control group), and augmented reality exergame (Portable Exergame Platform for Elderly) sessions. The participants were randomized in a within-group design into one of six possible combinations.

Real-Time Ship Segmentation in Maritime Surveillance Videos Using Automatically Annotated Synthetic Datasets.

This work proposes a new system capable of real-time ship instance segmentation during maritime surveillance missions by unmanned aerial vehicles using an onboard standard RGB camera. The implementation requires two stages: an instance segmentation network able to produce fast and reliable preliminary segmentation results and a post-processing 3D fully connected Conditional Random Field, which significantly improves segmentation results by exploring temporal correlations between nearby frames in video sequences. Moreover, due to the absence of maritime datasets consisting of properly labeled video sequences, we create a new dataset comprising synthetic video sequences of maritime surveillance scenarios (MarSyn).

A low-cost virtual coach for 2D video-based compensation assessment of upper extremity rehabilitation exercises.

Background: The increasing demands concerning stroke rehabilitation and in-home exercise promotion grew the need for affordable and accessible assistive systems to promote patients' compliance in therapy. These assistive systems require quantitative methods to assess patients' quality of movement and provide feedback on their performance. However, state-of-the-art quantitative assessment approaches require expensive motion-capture devices, which might be a barrier to the development of low-cost systems.

Multispectral Facial Recognition in the Wild.

This work proposes a multi-spectral face recognition system in an uncontrolled environment, aiming to identify or authenticate identities (people) through their facial images. Face recognition systems in uncontrolled environments have shown impressive performance improvements over recent decades. However, most are limited to the use of a single spectral band in the visible spectrum.

Scalable Fire and Smoke Segmentation from Aerial Images Using Convolutional Neural Networks and Quad-Tree Search.

Autonomous systems can help firefighting operations by detecting and locating the fire spot from surveillance images and videos. Similar to many other areas of computer vision, Convolutional Neural Networks (CNNs) have achieved state-of-the-art results for fire and smoke detection and segmentation. In practice, input images to a CNN are usually downsized to fit into the network to avoid computational complexities and restricted memory problems.

Real-Time Georeferencing of Fire Front Aerial Images Using Iterative Ray-Tracing and the Bearings-Range Extended Kalman Filter.

Although Aerial Vehicle images are a viable tool for observing large-scale patterns of fires and their impacts, its application is limited by the complex optical georeferencing procedure due to the lack of distinctive visual features in forest environments. For this reason, an exploratory study on rough and flat terrains was conducted to use and validate the Iterative Ray-Tracing method in combination with a Bearings-Range Extended Kalman Filter as a real-time forest fire georeferencing and filtering algorithm on images captured by an aerial vehicle. The Iterative Ray-Tracing method requires a vehicle equipped with a Global Positioning System (GPS), an Inertial Measurement Unit (IMU), a calibrated camera, and a Digital Elevation Map (DEM).

A Soft Tactile Sensor Based on Magnetics and Hybrid Flexible-Rigid Electronics.

Tactile sensing is crucial for robots to manipulate objects successfully. However, integrating tactile sensors into robotic hands is still challenging, mainly due to the need to cover small multi-curved surfaces with several components that must be miniaturized. In this paper, we report the design of a novel magnetic-based tactile sensor to be integrated into the robotic hand of the humanoid robot Vizzy.

Multispectral Face Recognition Using Transfer Learning with Adaptation of Domain Specific Units.

Facial recognition is a method of identifying or authenticating the identity of people through their faces. Nowadays, facial recognition systems that use multispectral images achieve better results than those that use only visible spectral band images. In this work, a novel architecture for facial recognition that uses multiple deep convolutional neural networks and multispectral images is proposed.

Modelling 3D saccade generation by feedforward optimal control.

An interesting problem for the human saccadic eye-movement system is how to deal with the degrees-of-freedom problem: the six extra-ocular muscles provide three rotational degrees of freedom, while only two are needed to point gaze at any direction. Measurements show that 3D eye orientations during head-fixed saccades in far-viewing conditions lie in Listing's plane (LP), in which the eye's cyclotorsion is zero (Listing's law, LL). Moreover, while saccades are executed as single-axis rotations around a stable eye-angular velocity axis, they follow straight trajectories in LP.

Break the Ice: a Survey on Socially Aware Engagement for Human-Robot First Encounters.

Society is starting to come up with exciting applications for social robots like butlers, coaches, and waiters. However, these robots face a challenging task: to meet people during a first encounter. This survey explores the literature that contributes to this task.

Markerless Eye-Hand Kinematic Calibration on the iCub Humanoid Robot.

Humanoid robots are resourceful platforms and can be used in diverse application scenarios. However, their high number of degrees of freedom (, moving arms, head and eyes) deteriorates the precision of eye-hand coordination. A good kinematic calibration is often difficult to achieve, due to several factors, , unmodeled deformations of the structure or backlash in the actuators.

Matrix Completion for Weakly-Supervised Multi-Label Image Classification.

In the last few years, image classification has become an incredibly active research topic, with widespread applications. Most methods for visual recognition are fully supervised, as they make use of bounding boxes or pixelwise segmentations to locate objects of interest. However, this type of manual labeling is time consuming, error prone and it has been shown that manual segmentations are not necessarily the optimal spatial enclosure for object classifiers.

Calibration of an outdoor distributed camera network with a 3D point cloud.

Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network.

Language bootstrapping: learning word meanings from perception-action association.

We address the problem of bootstrapping language acquisition for an artificial system similarly to what is observed in experiments with human infants. Our method works by associating meanings to words in manipulation tasks, as a robot interacts with objects and listens to verbal descriptions of the interactions. The model is based on an affordance network, i.

The iCub humanoid robot: an open-systems platform for research in cognitive development.

We describe a humanoid robot platform--the iCub--which was designed to support collaborative research in cognitive development through autonomous exploration and social interaction. The motivation for this effort is the conviction that significantly greater impact can be leveraged by adopting an open systems policy for software and hardware development. This creates the need for a robust humanoid robot that offers rich perceptuo-motor capabilities with many degrees of freedom, a cognitive capacity for learning and development, a software architecture that encourages reuse & easy integration, and a support infrastructure that fosters collaboration and sharing of resources.

A fluorescent mutant of the NM domain of the yeast prion Sup35 provides insight into fibril formation and stability.

The Sup35 protein of Saccharomyces cerevisiae forms a prion that generates the [PSI(+)] phenotype. Its NM region governs prion status, forming self-seeding amyloid fibers in vivo and in vitro. A tryptophan mutant of Sup35 (NM(F117W)) was used to probe its aggregation.

Fast IIR isotropic 2-D complex Gabor filters with boundary initialization.

Gabor filters are widely applied in image analysis and computer vision applications. This paper describes a fast algorithm for isotropic complex Gabor filtering that outperforms existing implementations. The main computational improvement arises from the decomposition of Gabor filtering into more efficient Gaussian filtering and sinusoidal modulations.