Antonio Greco

Antonio Greco
Università degli Studi di Salerno | UNISA · Department of Information Engineering, Electrical Engineering and Applied Mathematics (DIEM)

Assistant Professor

About

45
Publications
13,462
Reads
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542
Citations
Introduction
I received the Ph.D. degree in Computer Science and Computer Engineering from the University of Salerno, Italy, in March 2018. I am currently an Assistant Professor at the University of Salerno. My research activities are mainly focused in the areas of Computer Vision and Pattern Recognition for detecting events of interest (especially related to face analysis) in real time on embedded systems with reduced computation resources as smart cameras, drones, robots.
Additional affiliations
March 2020 - present
Università degli Studi di Salerno
Position
  • Professor (Assistant)
April 2018 - February 2020
Università degli Studi di Salerno
Position
  • PostDoc Position
Education
December 2014 - March 2018
Università degli Studi di Salerno
Field of study
  • Computer Engineering

Publications

Publications (45)
Article
Full-text available
Hand washing preparation can be considered as one of the main strategies for reducing the risk of surgical site contamination and thus the infections risks. Within this context, in this paper we propose an embedded system able to automatically analyze, in real-time, the sequence of images acquired by a depth camera to evaluate the quality of the ha...
Article
Full-text available
Emotion recognition from face images is a challenging task that gained interest in recent years for its applications to business intelligence and social robotics. Researchers in computer vision and affective computing focused on optimizing the classification error on benchmark data sets, which do not extensively cover possible variations that face...
Article
Full-text available
In the era of deep learning, the methods for gender recognition from face images achieve remarkable performance over most of the standard datasets. However, the common experimental analyses do not take into account that the face images given as input to the neural networks are often affected by strong corruptions not always represented in standard...
Article
Full-text available
Massive open online courses (MOOCs) allow students and instructors to discuss through messages posted on a forum. However, the instructors should limit their interaction to the most critical tasks during MOOC delivery so, teacher-led scaffolding activities, such as forum-based support, can be very limited, even impossible in such environments. In a...
Experiment Findings
Full-text available
Chapter
Guess The Age 2021 is an international contest meant for teams able to propose methods based on modern Deep Convolutional Neural Networks (DCNNs) for age estimation from facial images. In order to allow the teams to train effective models, the Mivia Age Dataset, including 575.073 images annotated with age labels, was provided as training set; it is...
Experiment Findings
Article
Full-text available
In the last years, a big interest of both the scientific community and the market has been devoted to the design of audio surveillance systems, able to analyse the audio stream and to identify events of interest; this is particularly true in security applications, in which the audio analytics can be profitably used as an alternative to video analyt...
Article
Video analytics can be profitably adopted in smart roads environments to automatically detect abnormal situations. Within this context, vehicle detection is the first and foremost stage, and its accuracy is crucial, since any detection error will affect the performance of any subsequent step. Furthermore, in smart road environments it is often pref...
Article
Full-text available
Age estimation from face images can be profitably employed in several applications, ranging from digital signage to social robotics, from business intelligence to access control. Only in recent years, the advent of deep learning allowed for the design of extremely accurate methods based on convolutional neural networks (CNNs) that achieve a remarka...
Chapter
Polypharmacy is the combined use of multiple drugs, widely adopted in medicine to treat patients that suffer of complex diseases. Therefore, it is important to have reliable tools able to predict if the activity of a drug could unfavorably change when combined with others. State-of-the-art methods face this problem as a link prediction task on a mu...
Chapter
Subgraph isomorphism is one of the most challenging problems on graph-based representations. Despite many efficient sequential algorithms have been proposed over the last decades, solving this problem on large graphs is still a time demanding task. For this reason, there is a recently growing interest in realizing effective parallel algorithms able...
Chapter
In retail environments, it is important to acquire information about customers entering in a selling area, by counting them, but also by understanding stable traits (such as gender, age, or ethnicity) and temporary feelings (such as the emotion). Anyway, in the last year, due to the COVID-19 pandemic, it is becoming mandatory to wear a mask, coveri...
Article
Full-text available
Although in recent years we have witnessed an explosion of the scientific research in the recognition of facial soft biometrics such as gender, age and expression with deep neural networks, the recognition of ethnicity has not received the same attention from the scientific community. The growth of this field is hindered by two related factors: on...
Article
Full-text available
Gender recognition has been among the most investigated problems in the last years; although several contributions have been proposed, gender recognition in unconstrained environments is still a challenging problem and a definitive solution has not been found yet. Furthermore, Deep Convolutional Neural Networks (DCNNs) achieve very interesting perf...
Article
Full-text available
In recent years we have assisted to a growing interest for embedded vision, due to the availability of low cost hardware systems, effective for energy consumption, flexible for their size at the cost of limited (compared to the server) computing resources. Their use is boosted by the simplicity of their positioning in places where energy or network...
Article
Audio surveillance is gaining in the last years wide interest. This is due to the large number of situations in which this kind of systems can be used, either alone or combined with video-based algorithms. In this paper we propose a deep learning method to automatically recognize events of interest in the context of audio surveillance (namely screa...
Article
Full-text available
For several years, fault diagnosis of photovoltaic (PV) plants has been manually performed by the human operator by a visual inspection or automatically, by evaluating electrical measures collected by sensors mounted on each PV module. In recent years, a notable interest of the scientific community has been devoted towards the definition of algorit...
Conference Paper
Photovoltaic (PV) panels are a clean and widespread way to produce renewable energy from sunlight; at the same time, such plants require maintenance, since solar panels can be affected by many types of damaging factors and have a limited yet variable lifespan. With the impressive growth of such PV installations, it is in the public eye the need of...
Conference Paper
A social robot is able to perceive the information about the environment (both in terms of persons and objects populating the scene), to reason about the acquired information and to interact with the human in a proper way. Among the information required for the interaction with a human, the capability of analysing the emotion is surely among the mo...
Article
In this paper we introduce VF3-Light, a simplification of VF3, a recently introduced, general-purpose subgraph isomorphism algorithm. While VF3 has demonstrated to be very effective on several datasets, especially on very large and very dense graphs, we will show that on some classes of graphs, the full power of VF3 may become an overkill; indeed,...
Article
Face analysis includes a variety of specific problems as face detection, person identification, gender and ethnicity recognition; in the last two decades, significant research efforts have been devoted to the challenging task of age estimation from faces, as witnessed by the high number of published papers. The explosion of the deep learning paradi...
Conference Paper
The combination of artificial intelligence and robotics opens the way to disruptive future developments in the industrial and collaborative robotics. The recent advances of the deep learning technologies materialize the possibility to provide a robot perceptive and reasoning skills and, consequently, the capability to autonomously interact with a h...
Article
The automatic analysis of images acquired by cameras mounted on board of drones (flying cameras) is attracting many scientists working in the field of computer vision; the interest is related to the increasing need of algorithms able to understand the scenes acquired by flying cameras, by detecting the moving objects, calculating their trajectories...
Article
Graph matching algorithms are gaining more and more interest in the last years from different scientific communities; indeed, they allow comparing any kind of objects represented using their intrinsic structure, represented in terms of attributed relational graphs. The challenge is to make these algorithms able to provide solutions over huge graphs...
Article
The popularity and the appeal of systems which are able to automatically determine the gender from face images is growing rapidly. Such a great interest arises from the wide variety of applications, especially in the fields of retail and video surveillance. In recent years there have been several attempts to address this challenge, but a definitive...
Conference Paper
Every year 424,000 fatal accidents occur, they are the second cause of unintentional death after road traffic injuries. The difference between fatal and not fatal accidents often is the presence of other people able to promptly provide first aid or call for help. Unfortunately, even during the practice of group activities (e.g. team sports) an acci...
Conference Paper
As reported by the World Health Organization, falls are a severe medical and financial issue; they represent the second leading cause of unintentional injury death, after road traffic injuries. Therefore, in recent years, the interest in realizing fall detection systems is considerably increased. Although the overall architecture of such systems in...
Conference Paper
Hot spots are among the defects of photovoltaic panels which may cause the most destructive effects. In this paper we propose a method able to automatically detect the hot spots in photovoltaic panels by analyzing the sequence of thermal images acquired by a camera mounted on board of a drone flighting over the plant. The main novelty of the propos...
Conference Paper
Full-text available
Gender recognition from face images is an important application in the fields of security, retail advertising and marketing. We propose a novel descriptor based on COSFIRE filters for gender recognition. A COSFIRE filter is train-able, in that its selectivity is determined in an automatic configuration process that analyses a given prototype patter...
Conference Paper
The recognition of gender from face images is an important application, especially in the fields of security, marketing and intelligent user interfaces. We propose an approach to gender recognition from faces by fusing the decisions of SVM classifiers. Each classifier is trained with different types of features, namely HOG (shape), LBP (texture) an...
Conference Paper
Full-text available
In this paper we present an innovative method for counting people from zenithal mounted cameras. The proposed method is designed to be computationally efficient and able to provide accurate counting under different realistic conditions. The method can operate with traditional surveillance cameras or with depth imaging sensors. The validation has be...
Conference Paper
Full-text available
In this paper we propose a method able to identify the presence of objects remaining motionless in the scene for a long time by analyzing the videos acquired by surveillance cameras. Our approach combines a background subtraction strategy with an enhanced tracking algorithm. The main contributions of this paper are the following: first, spatio-temp...
Conference Paper
Full-text available
In this paper we propose a novel method for detecting fires in both indoor and outdoor environments. The videos acquired by traditional surveillance cameras are analyzed and different typologies of information, respectively based on color and movement, are combined into a multi expert system in order to increase the overall reliability of the appro...

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Projects

Projects (6)
Project
Special Issue on Ambient Understanding for Mobile Autonomous Robots Journal of Ambient Intelligence and Humanized Computing (AIHC) Journal Impact Factor (2020): 7.104 (ISSN: 1868-5137) Website: https://www.springer.com/journal/12652/updates/19709550 Submission Deadline: 28th February 2022 Call for papers In recent years, the combination of robotics and artificial intelligence arose outstanding developments in the fields of cognitive robotics and human robot interaction. Nowadays several academic and industrial research groups are engaged in the design of intelligent robots able to act autonomously, by means of advanced deep learning algorithms used for the analysis of data acquired from heterogeneous sensors (camera, 3D camera, stereo camera, microphone, LIDAR, sonar etc.), for ambient understanding (people, objects, scenes) and for dynamically adapting the interaction with humans and environment. Despite the recent deep learning achievements and the impressive advances in technology for intelligent robot systems, there are still several challenges to be addressed in computer vision, audio analysis, sensor fusion, autonomous navigation methods and human robot interaction. Such challenges arise from the inherent difficulty of designing algorithms that are effective in the complex real world, but are also due to the acquisition of low quality or corrupted images, noisy audio and inaccurate data from environmental sensors, and to the necessity to process large amounts of operations in real-time. The aim of the special issue is to provide a collection of innovative algorithms, theories and applications related to all the aspects of perception, reasoning and navigation of a mobile autonomous robot, with contributions from both academia and industry. Even the submission of datasets and benchmarks collected in real challenging conditions or methods optimized for real-time perception and reasoning are encouraged. Topics of interest are, but not limited to: • Face Analysis (Detection, Recognition, Re-Identification, Gender, Age, Ethnicity, Emotion) • People detection • 2D and 3D object detection and recognition for ambient understanding and reconstruction • 6D Pose Estimation • Gesture and action recognition • Voice and audio event detection and localization • Speech Analysis for human-robot interaction (Speaker Recognition, Gender, Age, Language, Emotion, Speech to text, Natural Language Processing) • Multi-modal perception for human-robot interaction and autonomous navigation • Ambient understanding for SLAM, dynamic motion planning and autonomous navigation • Reinforcement learning for cognitive robotics • Datasets and benchmarks in the wild • Software optimization for real-time perception, reasoning and navigation • Embedded systems for cognitive robotics • Algorithms for autonomous car driving Guest editors Antonio Greco (Università degli Studi di Salerno, Italy) Mario Vento (Università degli Studi di Salerno, Italy) Sean Ryan Fanello (Google, USA)
Project
Website: http://gta2021.unisa.it Submission deadline: June 30th, 2021 The Guess The Age (GTA) Contest will be held by the 19th International Conference on Computer Analysis of Images and Patterns CAIP 2021. GTA is an International Contest on Age Estimation from Facial Images with Deep Convolutional Neural Networks (DCNNs). The participants will receive a new dataset, the Mivia Age Dataset, including 575.073 images annotated with age labels; it is among the biggest publicly available datasets of faces in the world with age annotations. With this dataset, the participants can train effective age estimation models, proposing novel DCNN architectures based a single neural networks or defining innovative training procedures for standard DCNN architectures. The performance of the proposed methods will be evaluated in terms of accuracy and regularity on a test set of more than 150.000 images, different from the ones available in the training set.
Project
The aim of the project is the design of novel methods for detecting and recognizing audio events of interest