When I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking

in Sensors (2020), 20(13), 3739

The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific ... [more ▼]

The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific literature as gaze tracking. This has become a very hot topic in the field of computer vision during the last decades, with a surprising and continuously growing number of application fields. A very long journey has been made from the first pioneering works, and this continuous search for more accurate solutions process has been further boosted in the last decade when deep neural networks have revolutionized the whole machine learning area, and gaze tracking as well. In this arena, it is being increasingly useful to find guidance through survey/review articles collecting most relevant works and putting clear pros and cons of existing techniques, also by introducing a precise taxonomy. This kind of manuscripts allows researchers and technicians to choose the better way to move towards their application or scientific goals. In the literature, there exist holistic and specifically technological survey documents (even if not updated), but, unfortunately, there is not an overview discussing how the great advancements in computer vision have impacted gaze tracking. Thus, this work represents an attempt to fill this gap, also introducing a wider point of view that brings to a new taxonomy (extending the consolidated ones) by considering gaze tracking as a more exhaustive task that aims at estimating gaze target from different perspectives: from the eye of the beholder (first-person view), from an external camera framing the beholder’s, from a third-person view looking at the scene where the beholder is placed in, and from an external view independent from the beholder. [less ▲]

Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers

in IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society (2019, October)

The reliability of aircraft inspection is of paramountimportance to safety of flights. Continuing airworthiness of air-craft structures is largely based upon the visual detection of smalldefects made by ... [more ▼]

The reliability of aircraft inspection is of paramountimportance to safety of flights. Continuing airworthiness of air-craft structures is largely based upon the visual detection of smalldefects made by trained inspection personnel with expensive,critical and time consuming tasks. At this aim, Unmanned AerialVehicles (UAVs) can be used for autonomous inspections, aslong as it is possible to localize the target while flying aroundit and correct the position. This work proposes a solution todetect the airplane pose with regards to the UAVs position whileflying autonomously around the airframe at close range forvisual inspection tasks. The system works by processing imagescoming from an RGB camera mounted on board, comparingincoming frames with a database of natural landmarks whoseposition on the airframe surface is known. The solution has beentested in real UAV flight scenarios, showing its effectiveness inlocalizing the pose with high precision. The advantages of theproposed methods are of industrial interest since we remove manyconstraint that are present in the state of the art solutions. [less ▲]

Real-Time Human Head Imitation for Humanoid Robots

in Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality (2019, July)

The ability of the robots to imitate human movements has been an active research study since the dawn of the robotics. Obtaining a realistic imitation is essential in terms of perceived quality in human ... [more ▼]

The ability of the robots to imitate human movements has been an active research study since the dawn of the robotics. Obtaining a realistic imitation is essential in terms of perceived quality in human-robot interaction, but it is still a challenge due to the lack of effective mapping between human movements and the degrees of freedom of robotics systems. If high-level programming interfaces, software and simulation tools simplified robot programming, there is still a strong gap between robot control and natural user interfaces. In this paper, a system to reproduce on a robot the head movements of a user in the field of view of a consumer camera is presented. The system recognizes the presence of a user and its head pose in real-time by using a deep neural network, in order to extract head position angles and to command the robot head movements consequently, obtaining a realistic imitation. At the same time, the system represents a natural user interface to control the Aldebaran NAO and Pepper humanoid robots with the head movements, with applications in human-robot interaction. [less ▲]

Flexible body scanning without template models

in Signal Processing (2019), 154

The apparition of low-cost depth cameras has lead to the development of several reconstruction methods that work well with rigid objects, but tend to fail when used to manually scan a standing person ... [more ▼]

The apparition of low-cost depth cameras has lead to the development of several reconstruction methods that work well with rigid objects, but tend to fail when used to manually scan a standing person. Specific methods for body scanning have been proposed, but they have some ad-hoc requirements that make them unsuitable in a wide range of applications: they either require rotation platforms, multiple sensors and a priori template model. Scanning a person with a hand-held low-cost depth camera is still a challenging unsolved problem. This work proposes a novel solution to easily scan standing persons by combining depth information with fiducial markers without using a template model. In our approach, a set of markers placed in the ground are used to improve camera tracking by a novel algorithm that fuses depth information with the known location of the markers. The proposed method analyzes the video sequence and automatically divides it into fragments that are employed to build partial overlapping scans of the subject. Then, a registration step (both rigid and non-rigid) is applied to create a final mesh of the scanned subject. The proposed method has been compared with the state-of-the-art KinectFusion [1], ElasticFusion [2], ORB-SLAM [3, 4], and BundleFusion [5] methods, exhibiting superior performance. [less ▲]

Video Indexing Using Face Appearance and Shot Transition Detection

in Proceedings of the IEEE International Conference on Computer Vision Workshops (2019)

An image processing pipeline to segment iris for unconstrained cow identification system

in Open Computer Science (2019), 9(1), 145--159

An Ecological Visual Exploration Tool to Support the Analysis of Visual Processing Pathways in Children with Autism Spectrum Disorders

in Journal of Imaging (2018)

Recent improvements in the field of assistive technologies have led to innovative solutions aiming at increasing the capabilities of people with disability, helping them in daily activities with ... [more ▼]

Recent improvements in the field of assistive technologies have led to innovative solutions aiming at increasing the capabilities of people with disability, helping them in daily activities with applications that span from cognitive impairments to developmental disabilities. In particular, in the case of Autism Spectrum Disorder (ASD), the need to obtain active feedback in order to extract subsequently meaningful data becomes of fundamental importance. In this work, a study about the possibility of understanding the visual exploration in children with ASD is presented. In order to obtain an automatic evaluation, an algorithm for free (i.e., without constraints, nor using additional hardware, infrared (IR) light sources or other intrusive methods) gaze estimation is employed. Furthermore, no initial calibration is required. It allows the user to freely rotate the head in the field of view of the sensor, and it is insensitive to the presence of eyeglasses, hats or particular hairstyles. These relaxations of the constraints make this technique particularly suitable to be used in the critical context of autism, where the child is certainly not inclined to employ invasive devices, nor to collaborate during calibration procedures.The evaluation of children’s gaze trajectories through the proposed solution is presented for the purpose of an Early Start Denver Model (ESDM) program built on the child’s spontaneous interests and game choice delivered in a natural setting. [less ▲]