Marcelo Saval-Calvo

• PhD Computer Vision
• Professor (Associate) at University of Alicante

Three-dimensional registration is an established yet challenging problem that is key in many different applications, such as mapping the environment for autonomous vehicles, or modeling people for avatar creation, among others. Registration refers to the process of mapping multiple data into the same coordinate system by means of matching correspon...

Medical image datasets are essential for training models used in computer-aided diagnosis, treatment planning, and medical research. However, some challenges are associated with these datasets, including variability in data distribution, data scarcity, and transfer learning issues when using models pre-trained from generic images. This work studies...

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...

Medical image classification datasets usually have a limited availability of annotated data, and pathological samples are usually much scarcer than healthy cases. Furthermore, data is often collected from different sources with different acquisition devices and population characteristics, making the trained models highly dependent on the data domai...

The study of tracts—bundles of nerve fibers that are organized together and have a similar function—is of major interest in neurology and related areas of science. Tractography is the medical imaging technique that provides the information to estimate these tracts, which is crucial for clinical applications and scientific research. This is a comple...

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...

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...

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...

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...

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...

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...

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...

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...

Visual servoing is a well-known task in robotics. However, there are still challenges when multiple sources are combined to accurately guide the robot or occlusions appear. In this paper we present a novel visual servoing approach using hybrid multi-camera input data to lead a robot arm accurately to dynamically moving target points in the presence...

Visual servoing is a well-known task in robotics. However, there are still challenges when multiple visual sources are combined to accurately guide the robot or occlusions appear. In this paper we present a novel visual servoing approach using hybrid multi-camera input data to lead a robot arm accurately to dynamically moving target points in the p...

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 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 problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but with different characteristics, and proposes a method for dynamic best viewpoint recovery of a target point while avoiding possible occlusions. Since the environment can c...

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...

The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but with different characteristics. It proposes a method for dynamic next best viewpoint recovery of a target point while avoiding possible occlusions. Since the environment c...

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...

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...

The use of visual information is a very well known input from different kinds of sensors. However, most of the perception problems are individually modeled and tackled. It is necessary to provide a general imaging model that allows us to parametrize different input systems as well as their problems and possible solutions. In this paper, we present...

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 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...

In this work, we propose a new dataset for 3D object recognition using the new high-resolution Kinect V2 sensor and some other popular low-cost devices like PrimeSense Carmine. Since most already existing datasets for 3D object recognition lack some features such as 3D pose information about objects in the scene, per pixel segmentation or level of...

Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many ap...

Autonomous vehicle systems are currently the object of intense research within scientific and industrial communities; however, many problems remain to be solved. One of the most critical aspects addressed in both autonomous driving and robotics is environment perception, since it consists of the ability to understand the surroundings of the vehicle...

In this paper we present a method for autofocusing images of sputum smears taken from a microscope which combines the finding of the optimal focus distance with an algorithm for extending the depth of field (EDoF). Our multifocus fusion method produces an unique image where all the relevant objects of the analyzed scene are well focused, independen...

RGB-D (Red Green Blue and Depth) sensors are devices that can provide color and depth information from a scene at the same time. Recently, they have been widely used in many solutions due to their commercial growth from the entertainment market to many diverse areas (e.g., robotics, CAD, etc.). In the research community, these devices have had good...

Many applications in computer vision require a high computational time for their processing. In general terms, those applications carry out several basic morphological real-time convolutions which are highly parallelizable. Using the above-mentioned convolutions along with a stack of images obtained with a digital microscope with different focusing...

Initially, building automation services were provided for larger buildings by means of a set of non-integrated subsystems. By the late 20th century, the concept had developed to include home automation through concepts such as the Digital Home, eHome or iHome based on smart systems and which supported the evolution of the traditional automation ser...

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,...

Registration of multiple sets of data into a common coordinate system is an important problem in many areas of computer vision and robotics. Usually a large set of data is involved in the process. Moreover, the sets are in general composed by a large number of 3D points. The input for registration techniques based on point set as inputs make someti...

Self-Organizing maps (SOM) are able to preserve topological information in the projecting space. Structure and learning algorithm of SOMs restrict the topological preservation in the map. Adjacent neurons share similar vector features. However, topological preservation from the input space is not always accomplished. In this paper, we propose a nov...

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...

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is st...

The automatic understanding of the behaviour conducted by humans in scenarios using images as input of the system is a very important and challenging problem involving different areas of computational intelligence. In this paper human activity recognition is studied from a prediction point of view. We propose a model that, in addition to the capabi...

The use of RBG-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has been increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and colour information using the same device. In this paper, we present a comparative analysis of the most important methods us...

La incorporación del EEES provocó una infinidad de desafíos y retos a las Universidades que a día de hoy aún están siendo solucionados. Además, ha conllevado nuevas oportunidades para la formación de estudiantes pero también para las Universidades. Entre ellas, la formación interuniversitaria entre estados miembro de la UE. El EEES permite unificar...

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representatio...

Registration is a main task in 3D objects reconstruction. Different approaches have been developed in order to solve specific problems in scenarios, objects or even the source of data. Recently, new problems have been appeared with the increasing use of low-cost RGB-D sensors. Registering small objects acquired by these cameras using traditional me...

In this chapter, a comparative analysis of basic segmentation methods of video sequences and their combinations is carried out. Analysis of different algorithms is based on the efficiency (true positive and false positive rates) and temporal cost to provide regions in the scene. These are two of the most important requirements of the design to prov...