Jorge Azorin-Lopez

University of Alicante | UA · Computer Sciences and Computation

Chicken behavior recognition is crucial for a number of reasons, including promoting animal welfare, ensuring the early detection of health issues, optimizing farm management practices, and contributing to more sustainable and ethical poultry farming. In this paper, we introduce a technique for recognizing chicken behavior on edge computing devices...

Overexploitation of fisheries is a worldwide problem, which is leading to a large loss of diversity, and affects human communities indirectly through the loss of traditional jobs, cultural heritage, etc . To address this issue, governments have started accumulating data on fishing activities, to determine biomass extraction rates, and fisheries sta...

The increasing prevalence of obesity and overweight has become a major public health concern, contributing to a range of chronic diseases and diminishing quality of life. The COVID-19 pandemic has further highlighted the risks associated with obesity. In response, researchers are exploring innovative solutions to provide personalized treatments for...

The performance of manufacturing operations relies heavily on the operators’ performance. When operators begin to exhibit signs of fatigue, both their individual performance and the overall performance of the manufacturing plant tend to decline. This research presents a methodology for analyzing fatigue in assembly operations, considering indicator...

This paper presents an approach that utilizes deep recurrent neural networks to predict body shape changes in individuals undergoing dietetic treatment. It contributes to computational body modelling by offering a reliable tool that assists healthcare professionals in tailoring recommendations and motivating individuals to achieve their body shape...

Are deep learning techniques being applied to image classification of kidney tumours? This systematic review aims to explore papers using this novel scientific method of deep learning (DL) for the detection of kidney tumours in patients. We can start by arguing that this set of techniques is not widespread as only 8 papers have been found in the la...

This paper provides an overview of the current state-of-the-art in the field of 3D human body model estimation, reconstruction, and generation in computer vision. The paper focuses on the most widely used parametric and generative methods and their applications. The paper highlights the use of different input data formats, including 2D images, vide...

Reliable identification of bird species is a critical task for many applications, such as conservation biology, biodiversity assessments, and monitoring bird populations. However, identifying birds in the wild by visual observation can be time-consuming and prone to errors. There is a growing need for efficient and accurate bird recognition methods...

This paper presents an approach to image segmentation and classification algorithm where the dataset has only few images labelled, done intentionally. The method tries to classify only the few instances with enough quality in the image, the KeyFish. In order to not being punished with wrong false positives, it must learn the examples but not the co...

The evolution of augmented reality (AR), with an improvement in its usability, allows more users to interact with this type of devices such as the HoloLens 2. One of the main fields benefiting greatly of these advances is healthcare, particularly for rehabilitation and well being. In AR, users are able to see the real world, reducing potential dizz...

This paper introduces a multimodal dataset created for research on digital twins in the manufacturing domain. Digital twins refer to the digital representations of physical world objects, and they require data to be accurately modeled. By incorporating various data modes, the digital twin representations in computational environments can become mor...

Bird identification is an important task in wildlife monitoring and conservation. However, traditional methods for bird identification often require significant computational resources, making them impractical for use on edge computing devices. In this paper, we propose an image mosaicing-based method for bird identification on edge computing devic...

We describe a method for estimating parametric 3D models of the human body from RGB-D sensor scans. We estimate both the pose and shape of the body. Our method uses a minimization function that relies on distance calculations between points selected using nearest neighbors and angles between normals. In addition, the use of intermediate templates h...

Anomaly detection is the identification of events or observations that deviate from the expected behaviour of a given set of data. Its main application is the prediction of possible technical failures. In particular, anomaly detection on supercomputers is a difficult problem to solve due to the large scale of the systems and the large number of com...

Anthropometric analysis of the human body is gaining more and more attention in the field of computer vision due to its usefulness in fields such as nutrition, medicine, the fashion industry, and so on. This research presents a method for automatically obtaining anthropometric measurements of the human body using 3D models. The system can obtain an...

Public security is a concept that, in western societies, is not given enough importance since the crime rates are at socially acceptable levels. Nowadays, with the help of artificial intelligence methods, it is possible to detect abnormal behaviour patterns in groups of people. This information can then be used to predict what is happening or about...

The advent of Industry 4.0 is revolutionizing manufacturing processes through techniques that can optimize the decision-making based on manufacturing data. Monitoring the whole production process from raw material input to the final product includes the production process itself and the human resources that carry it out. One of the key aspects of t...

Fisheries around the world show an overexploitation, which has led communities to find management strategies to tackle the problem. However, strategies are often taken on the basis of statistical data of dubious real-world utility. To address this problem, accurate biomass extraction calculations are required. The fish market is the place where ves...

Anomaly detection is the identification of events or observations that deviate from the expected behaviour of a given set of data. Its main application is the prediction of possible technical failures. In particular, anomaly detection on supercomputers is a difficult problem to solve due to the large scale of the systems and the large number of com...

Currently, the ability to automatically detect human behavior in image sequences is one of the most important challenges in the area of computer vision. Within this broad field of knowledge, the recognition of activities of people groups in public areas is receiving special attention due to its importance in many aspects including safety and securi...

Preserving maritime ecosystems is a major concern for governments and administrations. Additionally, improving fishing industry processes, as well as that of fish markets, to have a more precise evaluation of the captures, will lead to a better control on the fish stocks. Many automated fish species classification and size estimation proposals have...

Artificial intelligence techniques have been increasingly applied in healthcare to help in many areas, from assisting clinical diagnoses to preventing diseases. In this paper, a machine learning approach to predict cholesterol levels using non-invasive and easy-to-collect data is presented. Specifically, it uses clinical and anthropometric data gat...

The assembly of products or components by operators in industries is a complex task with recurring problems. In these processes, operators often make errors that can lead to defective products. Therefore, they need to be inspected later to verify their correct assembly. The main problems are caused by several reasons including high employee turnove...

Nowadays, companies face new challenges and benefits with the incorporation of technologies associated with Industry 4.0 into product manufacturing. The new collaborative environments have to be capable of adapting efficiently to different levels of production as well as safely collaborating in the process with human operators. In this paper, a mod...

Product assembly is a crucial process in manufacturing plants. In Industry 4.0, the offer of mass-customized products is expanded, thereby increasing the complexity of the assembling phase. This implies that operators should pay close attention to small details, potentially resulting in errors during the manufacturing process owing to its high leve...

Planes are the core geometric models present everywhere in the three-dimensional real world. There are many examples of manual constructions based on planar patches: facades, corridors, packages, boxes, etc. In these constructions, planar patches must satisfy orthogonal constraints by design ( e.g . walls with a ceiling and floor). The hypothesis i...

Nowadays, the emergence of large-scale and highly distributed cyber-physical systems (CPSs) in applications including Internet of things (IoT), cloud computing, mobility, Big Data, and sensor networks involves that architecture models have to work in an open and highly dynamic world. This fact increasingly highlights the importance of designing rea...

The indigenous communities in the Amazonia are in an accelerated process of acculturation. In this context, one of the main elements in order to determine the cause and effect of migration would be to measure the degree of ethnic identity of each indigenous individual or an entire community as a whole. In this research, a study is carried out that...

Given the application domains and challenges presented to cyber-physical systems (CPSs), it is necessary to design a CPS system able to deal with temporal constrains. There are various software architecture models to meet this challenge. Models have been developed under three types of software structural units, such as: Component-based architecture...

The use of intelligent systems to improve manufacturing processes is the basis for the development of robotic solutions in Industry 4.0. Monitoring operators manipulating tools and objects is one of the key tasks. Deep learning methods are obtaining state-of-the-art results to solve this problem but large amounts of labelled data should be provided...

In factories, the assembly of products or components by operators is a complex task that is not free of recurring problems. In this process, operators often make mistakes that can lead to defective products. Therefore, they need to be inspected later to verify their correct assembly. The main problems are caused by several reasons, including high e...

Obtaining 3D measurements of the human body requires precise scanning of the body, as well as methods for extracting these 1D/2D and 3D measurements from the selected volumes. The analysis of these 3D measurements and their monitoring over time (4D) in patients undergoing dietary treatment is a field that poses multidisciplinary challenges such as...

Currently, the automation of activity recognition of a group of people in closed and open environments is a major problem, especially in video surveillance. It is becoming increasingly important to have computer vision architectures that allow automatic recognition of group activities to make decisions. This paper proposes a computer vision archite...

A critical review of works related to visual surveillance from an algorithmic point of view including detection, monitoring, and analysis of people's behavior is presented in this paper. On the other hand, the architectures of services for video surveillance are reviewed, making a critical analysis and presenting the challenges to be solved. In thi...

Cultural identity is a complex concept that includes subjective factors such as ideology, family knowledge, customs, language, and acquired skills, among others. Measuring culture involves a significant level of difficulty, since its study and scope differ from the point of view, the time and the place where the studies are carried out. In the Amaz...

This paper reviews recent deep learning-based registration methods. Registration is the process that computes the transformation that aligns datasets, and the accuracy of the result depends on multiple factors. The most significant factors are the size of input data; the presence of noise, outliers and occlusions; the quality of the extracted featu...

Confined space fires are common emergencies in our society. Enclosure size, ventilation, or type and quantity of fuel involved are factors that determine the fire evolution in these situations. In some cases, favourable conditions may give rise to a flashover phenomenon. However, The difficulty of handling this complicated emergency through fire se...

The first step towards a Smart Village is that the community itself can benefit from the novel techniques that are applied. Some communities are far from being able to use the benefits that these technologies usually offer, however they can benefit from the techniques that have led to the development of smart cities. This is the case of the indigen...

This research aims to improve dietetic-nutritional treatment using state-of-the-art RGB-D sensors and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved using multimedia technologies. However, there are few studies using 3D data and VR technologies for this purpose. On the other hand, obtaining 3D measu...

This research aims to improve dietetic-nutritional treatment using state-of-the-art RGB-D sensors and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved using multimedia technologies. However, there are few studies using 3D data and VR technologies for this purpose. On the other hand, obtaining 3D measu...

Registration is the process that computes the transformation that aligns sets of data. Commonly, a registration process can be divided into four main steps: target selection, feature extraction, feature matching, and transform computation for the alignment. The accuracy of the result depends on multiple factors, the most significant are the quantit...

At its conception mechatronics was viewed purely in terms of the ability to integrate the technologies of mechanical and electrical engineering with computer science to transfer functionality, and hence complexity, from the mechanical domain to the software domain. However, as technologies, and in particular computing technologies, have evolved so...

Gamification methods adapt the mechanics of games to educational environments for the improvement of the teaching-learning process. Serious games play an important role as tools for gamification, in particular in the context of software engineering courses because of the idiosyncratic nature of the topic. However, the studies on the improvement of...

There is a huge demand for new techniques and technologies to tackle life-threatening in fire emergencies. Enclosure fires are a type of emergency involving firefighters whose lives are sometimes put at risk. In any confined fire, the emergency team may encounter two types of combustion environments, ventilated or under-ventilated. The rapidly chan...

This research aims to improve adherence to dietetic-nutritional treatment using state-of-the-art RGB-D sensor and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved by using multimedia technologies which impact on the body awareness of patients. However, there are no studies published to date using 3D d...

Latin American Indians have undergone changes in their cultural identity, especially as a result of contact with Western cultures. In order to determine the degree of change in cultural identity, the authors have recently developed an instrument designed from an indigenous perspective that provides information on 30 subdimensions and 5 cultural dim...

Educational models are incorporating methodologies to train students in teamwork skills in response to companies’ information technology (IT) requirements. Conflict management is key to effective teamwork. This paper proposes a method to improve students’ organisation, teamwork and conflict management skills. This method consists of a brief trainin...

We consider the problem of processing point cloud sequences. In particular, we represent and track objects in dynamic scenes acquired using low-cost sensors such as the Kinect. An efficient neural network based approach is proposed to represent and estimate 3D objects motion. This system addresses multiple computer vision tasks such as object segme...

Many researches and applications are using low-cost RGB-D sensors for 3D data acquisition. In general terms, the registration problem tries to find a transformation between two coordinate systems that better aligns the point sets. In order to review and describe the state-of-the-art of the rigid registration approaches, the authors decided to class...

Distinguishing axons from central or peripheral nervous systems (CNS or PNS, respectively) is often a complicated task. The main objective of this work was to facilitate and support the process of automatically distinguishing the different types of nerve fibres by analysing their morphological characteristics. Our approach was based on a multi-leve...

Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate the transformation between two instances of a deforming structure. Despite many previous developments on this topic, it remains a challenging problem. In this paper we prop...

Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate the transformation between two instances of a deforming structure. Despite many previous developments on this topic, it remains a challenging problem. In this paper we prop...

The human behaviour analysis has been a subject of study in various fields of science (e.g. sociology, psychology, computer science). Specifically, the automated understanding of the behaviour of both individuals and groups remains a very challenging problem from the sensor systems to artificial intelligence techniques. Being aware of the extent of...

In the creation of new industries, products and services -- all of which are advances of the Fourth Industrial Revolution -- the human-robot interaction that includes automatic learning and computer vision are elements to consider since they promote collaborative environments between people and robots. The use of machine learning and computer visio...

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In...

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitor...

Many applications including object reconstruction, robot guidance, and scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown an it is necessary to apply expert inference to estimate them. In the last few years,...

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RA...

In the creation of new industries, products and services -- all of which are advances of the Fourth Industrial Revolution -- the human-robot interaction that includes automatic learning and computer vision are elements to consider since they promote collaborative environments between people and robots. The use of machine learning and computer visio...

In this paper, the problem of 3D body registration using a single RGB-D sensor is approached. It has been guided by three main requirements: low-cost, unconstrained movement and accuracy. In order to fit them, an iterative registration method for accurately aligning data from single RGB-D sensor is proposed. The data is acquired while a person rota...