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52 Papers

A Preliminary Development of the Morris Maze Procedure in Virtual Reality

Topics: Augmented, Mixed and Virtual Environments; Hardware Technologies for Augmented, Mixed and Virtual Environments; Virtual Reality Tools and Languages; Human Performance and Usability of Virtual Environments

Authors: Jesús Moreno ¹ , Juan Jurado ¹ , José Callejas-Aguilera ² and J. Jiménez-Pérez ¹

Affiliations: ¹ Computer Graphics and Geomatics Group, University of Jaén, Jaén, Spain , ² Psychology, University of Jaén, Jaén, Spain

Digital Object Identifier: 10.5220/0010897500003124

Proceedings of GRAPP 2022, ISBN: 978-989-758-555-5

Quick Abstract

The Morris Water Maze (MWM) has become one of the most widely used laboratory tools in behavioural neuroscience. It has been used in some of the most sophisticated experiments in the study of spatial learning and memory with animals. However, human-based studies have been very limited due to the use of unrealistic scenarios, usually presented on a computer screen where participants’ attention is poorly controlled. Recent advances in virtual reality (VR) enable the generation of 3D environments with a high level of realism and user’s immersion. The user’s attention plays a key role in spatial learning. Current VR systems integrate eye-tracking devices to measure the user’s attention over virtual entities. In this paper, we present an easy-to-use game-based simulator of the MWM, using eye-tracking VR technology to extract information about the user’s attention. This research still in progress has achieved important hints according to the design of the virtual scenario, user interaction and experimentation. The study conducted in this paper validates the technology as a novel way to perform MWM focused on spatial learning and memory with human participants.

A Proposal to Improve Voice-based Interfaces for Elders using Daily-living Activity Identification

Topics: Improving eHealth through games; HCI for elderly people; Games for seniors and the elderly

Authors: Fernando Martínez-Santiago , Rosario García-Viedma , Antonio Rueda-Ruíz , Manuel Ureña-Cámara , Ángel-Luis García-Fernández and L. Ureña-López

Affiliation: Centro de Estudios Avanzados de las Tecnologías de la Información, Universidad de Jaén, Spain

Digital Object Identifier: 10.5220/0009817703010307

Proceedings of TEG 2020, ISBN: 978-989-758-420-6

Quick Abstract

It is a matter of common knowledge that the aging process entails a cognitive decline in certain processes such as attention, episodic memory, working memory, processing speed and executive functions. In recent years, efforts have been made to study the potential of Information and Communication Technologies to improve cognitive functioning and quality of life in elderly adults with and without cognitive impairments. In this paper, we introduce CODA (COgnitive Decline Alert kit), a system intended to keep record of the activities of daily living that also implements straightforward games heavily based on voice assistants that get leverage of such records with two main aims: the first one is to achieve a engaging gaming experience, by means of the introduction of questions related with activities of daily living that have been carried out recently by the elder. The second one is to have a means to evaluate the memory processes of the elder by analyzing their answers to the game questions; these are expected to be a useful source of information about the cognitive decline of the person.

Virtual Reality Environment for the Validation of Bone Fracture Reduction Processes

Topics: Augmented, Mixed and Virtual Environments; Simulation for Education and Training; Games for Education and Training; Human Performance and Usability of Virtual Environments

Authors: J. Jiménez-Delgado , A. Calzado-Martínez , F. Pérez-Cano and A. Luque-Luque

Affiliation: Graphics and Geomatics Group, University of Jaén, Jaén, Spain

Digital Object Identifier: 10.5220/0009175003990405

Proceedings of GRAPP 2020, ISBN: 978-989-758-402-2

Quick Abstract

This work presents a virtual environment for the validation by experts of computer-assisted bone fracture reduction. This environment is composed of VR glasses and 3D controllers (HTC Vive) that allow interaction and immersion in the scene in a realistic way. The virtual environment developed allows loading fractured bone models (fragments) so that the specialist performs a virtual fracture reduction and its results can be used for the validation of algorithms and assisted reduction techniques. Once the fragments are loaded, the user can perform an interactive reduction of the fracture, visualizing the fragments in 3d from different views, moving the fragments in 3d and placing the fragments in space to observe the reduction in detail. Once completed, it allows the reduction to be exported so that it can be compared with other fracture reduction systems. The system has been tested by specialists in traumatology and a usability study has been carried out. Finally, the system has been empirically validated and used to compare the performance of other computer-assisted reduction systems.

Accurate Plant Modeling based on the Real Light Incidence

Topics: Modeling and Algorithms; Modeling of Natural Scenes and Phenomena; Image-Based Modeling; Solid and Heterogeneous Modeling; Procedural and Multiresolution Modeling

Authors: J. Jurado , J. Cárdenas , C. Ogayar , L. Ortega and F. Feito

Affiliation: Computer Graphics and Geomatics Group, University of Jaén and Spain

Digital Object Identifier: 10.5220/0007686803600366

Proceedings of GRAPP 2019, ISBN: 978-989-758-354-4

Quick Abstract

In this paper, we propose a framework for accurate plant modeling constrained to actual plant-light interaction along a time-interval. To this end, several plant models have been generated by using data from different sources such as LiDAR scanning, optical cameras and multispectral sensors. In contrast to previous approaches that mostly focus on realistic rendering purposes, the main objective of our method is to improve the multiview stereo reconstruction of plant structures and the prediction of the growth of existing plants according to the influence of real light incidence. Our experimental results are oriented to olive trees, which are formed by many thin branches and dense foliage. Plant reconstruction is a challenging task due to self-occlusion. Our approach is based on inverse modeling to generate a parametric model which describes how plants evolve in a time interval by considering the surrounding environment. A multispectral sensor has been used to characterize input plant models from reflectance values for each narrow-band. We propose the fusion of heterogeneous data to achieve a more accurate modeling of plant structure and the prediction of the branching fate.

Related Ontology Subjects/Areas/Topics (9)

Applications	Image-Based Modeling	Pattern Recognition
Computer Vision, Visualization and Computer Graphics	Modeling and Algorithms	Software Engineering
Geometry and Modeling	Modeling of Natural Scenes and Phenomena	Solid and Heterogeneous Modeling

Automatic Detection of Distal Humerus Features: First Steps

Topics: Modeling and Algorithms; Geometric Computing; Surface Modeling; Model Validation; Processing Frameworks and Data Structures

Authors: José Negrillo-Cárdenas , Juan-Roberto Jiménez-Pérez and Francisco Feito

Affiliation: Graphics and Geomatics Group of Jaén, University of Jaén, Campus Las Lagunillas S/N, Jaén and Spain

Digital Object Identifier: 10.5220/0007686103540359

Proceedings of GRAPP 2019, ISBN: 978-989-758-354-4

Quick Abstract

Identification of specific landmarks in tissues is fundamental for understanding the human anatomy in medical applications. Specifically, the assessment of bone features allows to detect several pathologies in orthopedics. The recognition has been formerly carried out via visual identification, providing insufficient accuracy. Automatic solutions are required to improve the precision and minimize diagnostic and surgical planning time. In this paper, we study distal humerus landmarks and a new algorithm to automatically detect them in a reasonable time. Our technique does not require a prior training, as a geometrical approach with a spatial decomposition is used to explore several regions of interest of the bone. Finally, a set of experiments are performed, showing promising results.

Related Ontology Subjects/Areas/Topics (6)

Computer Vision, Visualization and Computer Graphics		Geometry and Modeling		Modeling and Algorithms
Geometric Computing		Model Validation		Surface Modeling

Optimal Filtering Algorithm based on Covariance Information using a Sequential Fusion Approach

Topic: System Modeling

Authors: R. Caballero-Águila ¹ , A. Hermoso-Carazo ² and J. Linares-Pérez ²

Affiliations: ¹ Departamento de Estadística e I.O., Universidad de Jaén, Campus Las Lagunillas s/n, 23071 Jaén and Spain , ² Departamento de Estadística e I.O., Universidad de Granada, Campus Fuentenueva s/n, 18071 Granada and Spain

Digital Object Identifier: 10.5220/0007786405870594

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

Quick Abstract

The least-squares linear filtering problem is addressed for discrete-time stochastic signals, whose evolution model is unknown and only the mean and covariance functions of the processes involved in the sensor measurement equations are available instead. The sensor measured outputs are perturbed by additive noise and different uncertainties, which are modelled in a unified way by random parameter matrices. Assuming that, at each sampling time, the noises from the different sensors are cross-correlated with each other, the sequential fusion architecture is adopted and the innovation technique is used to derive an easily implementable recursive filtering algorithm. A simulation example is included to verify the effectiveness of the proposed sequential fusion filter and analyze the influence of the sensor disturbances on the filter performance.

Related Ontology Subjects/Areas/Topics (3)

Informatics in Control, Automation and Robotics

Signal Processing, Sensors, Systems Modeling and Control

System Modeling

Signal Estimation with Random Parameter Matrices and Time-correlated Measurement Noises

Topic: System Modeling

Authors: R. Caballero-Águila ¹ , A. Hermoso-Carazo ² and J. Linares-Pérez ²

Digital Object Identifier: 10.5220/0007807804810487

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

Quick Abstract

This paper is concerned with the least-squares linear estimation problem for a class of discrete-time networked systems whose measurements are perturbed by random parameter matrices and time-correlated additive noise, without requiring a full knowledge of the state-space model generating the signal process, but only information about its mean and covariance functions. Assuming that the measurement additive noise is the output of a known linear system driven by white noise, the time-differencing method is used to remove this time-correlated noise and recursive algorithms for the linear filtering and fixed-point smoothing estimators are obtained by an innovation approach. These estimators are optimal in the least-squares sense and, consequently, their accuracy is evaluated by the estimation error covariance matrices, for which recursive formulas are also deduced. The proposed algorithms are easily implementable, as it is shown in the computer simulation example, where they are applied to estimate a signal from measured outputs which, besides including time-correlated additive noise, are affected by the missing measurement phenomenon and multiplicative noise (random uncertainties that can be covered by the current model with random parameter matrices). The computer simulations also illustrate the behaviour of the filtering estimators for different values of the missing measurement probability.

Related Ontology Subjects/Areas/Topics (3)

Informatics in Control, Automation and Robotics

Signal Processing, Sensors, Systems Modeling and Control

System Modeling

Towards the Modelling of Osseous Tissue

Topics: Modeling and Algorithms; Image-Based Modeling; Surface Modeling; Model Validation

Authors: F. Pérez and J. Jiménez

Affiliation: Graphics and Geomatics Group, University of Jaén, Jaén and Spain

Digital Object Identifier: 10.5220/0007580803400345

Proceedings of GRAPP 2019, ISBN: 978-989-758-354-4

Quick Abstract

The virtual representation of bone tissue is one of the pending challenges of infographics in the field of traumatology. This advance could mean a reduction in the time and effort that is currently used in the analysis of a bank of medical images, as it is done manually. Our proposal aims to lay the foundations of the elements that must be taken into account not only geometrically, but also from a medical point of view. In this article we focus on the segmentation of a bone model, establish the limits for its representation and introduce the main characteristics of the microstructures that form in the bone tissue.

Related Ontology Subjects/Areas/Topics (9)

Applications	Image-Based Modeling	Pattern Recognition
Computer Vision, Visualization and Computer Graphics	Model Validation	Software Engineering
Geometry and Modeling	Modeling and Algorithms	Surface Modeling

Initial Results of a Method for the Generation of Triangle Meshes Representing Bone Fragments using a Spatial Decomposition

Topics: Scene and Object Modeling; Image-Based Modeling; Solid and Heterogeneous Modeling; Geometric Computing; CAGD/CAD/CAM Systems

Authors: Félix Paulano-Godino and Juan J. Jiménez-Delgado

Affiliation: University of Jaén, Spain

Digital Object Identifier: 10.5220/0006266302980305

Proceedings of GRAPP 2017/VISIGRAPP, ISBN: 978-989-758-224-0

Quick Abstract

The generation of a virtual representation of the bones and fragments is an artificial step required in order to obtain helpful models to work with in a simulation. Nowadays, the Marching Cubes algorithm is a de facto standard for the generation of geometric models from medical images. However, bone fragments models generated by Marching Cubes are huge and contain many unconnected geometric elements inside the bone due to the trabecular tissue. The development of new methods to generate geometrically simple 3D models from CT image stacks that preserve the original information extracted from them would be of great interest. In order to achieve that, a preliminary study for the development of a new method to generate triangle meshes from segmented medical images is presented. The method does not modify the points extracted from CT images, and avoid generating triangles inside the bone. The aim of this initial study is to analyse if a spatial decomposition may help in the process of generating a triangle mesh by using a divide-and-conquer approach. The method is under development and therefore this paper only presents some initial results and exposes the detected issues to be improved.

Related Ontology Subjects/Areas/Topics (10)

Applications	Geometry and Modeling	Scene and Object Modeling
CAGD/CAD/CAM Systems	Image-Based Modeling	Software Engineering
Computer Vision, Visualization and Computer Graphics	Pattern Recognition	Solid and Heterogeneous Modeling
Geometric Computing

Ranking the Performance of Compiled and Interpreted Languages in Genetic Algorithms

Topics: Genetic Algorithms; Representation Techniques

Authors: Juan Julián Merelo-Guervós ¹ , Israel Blancas-Álvarez ¹ , Pedro A. Castillo ¹ , Gustavo Romero ¹ , Pablo García-Sánchez ¹ , Víctor M. Rivas ² , Mario García-Valdez ³ , Amaury Hernández-Águila ³ and Mario Román ¹

Affiliations: ¹ University of Granada, Spain , ² University of Jaén, Spain , ³ Tijuana Institute of Technology, Mexico

Digital Object Identifier: 10.5220/0006048101640170

Proceedings of ECTA 2016/IJCCI, ISBN: 978-989-758-201-1

Quick Abstract

Despite the existence and popularity of many new and classical computer languages, the evolu- tionary algorithm community has mostly exploited a few popular ones, avoiding them, especially if they are not compiled, under the asumption that compiled languages are always faster than interpreted languages. Wide-ranging performance analyses of implementation of evolutionary al- gorithms are usually focused on algorithmic implementation details and data structures, but these are usually limited to specific languages. In this paper we measure the execution speed of three common operations in genetic algorithms in many popular and emerging computer languages us- ing different data structures and implementation alternatives, with several objectives: create a ranking for these operations, compare relative speeds taking into account different chromosome sizes and data structures, and dispel or show evidence for several hypotheses that underlie most popular evolutionary algorithm libraries and applications. We find that there is indeed basis to consider compiled languages, such as Java, faster in a general sense, but there are other languages, including interpreted ones, that can hold its ground against them.

Related Ontology Subjects/Areas/Topics (8)

Artificial Intelligence	Genetic Algorithms	Representation Techniques
Computational Intelligence	Informatics in Control, Automation and Robotics	Soft Computing
Evolutionary Computing	Intelligent Control Systems and Optimization

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