Papers by Jorge Azorin-Lopez
2020 International Joint Conference on Neural Networks (IJCNN)
2018 International Joint Conference on Neural Networks (IJCNN)
2021 International Joint Conference on Neural Networks (IJCNN)
Computer Vision and Image Understanding
Research into object deformations using computer vision techniques has been under intense study i... more 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 propose a novel approach to non-rigid registration combining two data spaces in order to robustly calculate the correspondences and transformation between two data sets. In particular, we use point color as well as 3D location as these are the common outputs of RGB-D cameras. We have propose the Color Coherent Point Drift (CCPD) algorithm (an extension of the CPD method [1]). Evaluation is performed using synthetic and real data. The synthetic data includes easy shapes that allow evaluation of the effect of noise, outliers and missing data. Moreover, an evaluation of realistic figures obtained using Blensor is carried out. Real data acquired using a general purpose Primesense Carmine sensor is used to validate the CCPD for real shapes. For all tests, the proposed method is compared to the original CPD showing better results in registration accuracy in most cases.
IEEE Access
Educational models are incorporating methodologies to train students in teamwork skills in respon... more 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 training on leadership and management styles, with minimal extra work, followed by the signing of team contracts that outline group rules, promoting the assumption of responsibilities. The experimental results showed that this method reduced conflict rates, improved group communication and indirectly improved satisfaction, responsibility and motivation in work groups. Consequently, students' overall academic performance improved, both as a group and as individuals.
International Journal of Computer Vision and Image Processing
In the creation of new industries, products and services -- all of which are advances of the Four... more 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 vision provides the tools needed to increase productivity and minimizes delivery reaction times by assisting in the optimization of complex production planning processes. This review of the state of the art presents the main trends that seek to improve human-robot interaction in productive environments, and identifies challenges in research as well as in industrial - technological development in this topic. In addition, this review offers a proposal on the needs of use of artificial intelligence in all processes of industry 4.0 as a crucial linking element among humans, robots, intelligent and traditional machines; as well as a mechanism for qu...
International Journal of Computer Vision and Image Processing
In this paper, the problem of 3D body registration using a single RGB-D sensor is approached. It ... more 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 rotates in front of the camera, without the need of any external marker or constraint about its pose. The articulated alignment is carried out in a model-free approach in order to be more consistent with the real data. The iterative method is divided in stages, contributing to each other by the refinement of a specific part of the acquired data. The exploratory results validate the proposed method that is able to feed on itself in each iteration improving the final result by a progressive iteration, with the required precision under the conditions of affordability and unconstrained movement acquisition.
Sensors (Basel, Switzerland), Jan 22, 2017
The use of visual information is a very well known input from different kinds of sensors. However... more 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 an active vision model considering the imaging system as a whole (including camera, lighting system, object to be perceived) in order to propose solutions to automated visual systems that present problems that we perceive. As a concrete case study, we instantiate the model in a real application and still challenging problem: automated visual inspection. It is one of the most used quality control systems to detect defects on manufactured objects. However, it presents problems for specular products. We model these perception problems taking into account environmental conditions and camera parameters that allow a system to properly perceive t...
INTED2017 Proceedings, 2017
INTED2017 Proceedings, 2017
Sensors, 2017
RGB-D (Red Green Blue and Depth) sensors are devices that can provide color and depth information... more 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 uptake due to their acceptable level of accuracy for many applications and their low cost, but in some cases, they work at the limit of their sensitivity, near to the minimum feature size that can be perceived. For this reason, calibration processes are critical in order to increase their accuracy and enable them to meet the requirements of such kinds of applications. To the best of our knowledge, there is not a comparative study of calibration algorithms evaluating its results in multiple RGB-D sensors. Specifically, in this paper, a comparison of the three most used calibration methods have been applied to three different RGB-D sensors based on structured light and time-of-flight. The comparison of methods has been carried out by a set of experiments to evaluate the accuracy of depth measurements. Additionally, an object reconstruction application has been used as example of an application for which the sensor works at the limit of its sensitivity. The obtained results of reconstruction have been evaluated through visual inspection and quantitative measurements.
IFAC-PapersOnLine, 2016
As mechatronic devices and components become increasingly integrated with and within wider system... more As mechatronic devices and components become increasingly integrated with and within wider systems concepts such as Cyber-Physical Systems and the Internet of Things, designer engineers are faced with new sets of challenges in areas such as privacy. The paper looks at the current, and potential future, of privacy legislation, regulations and standards and considers how these are likely to impact on the way in which mechatronics is perceived and viewed. The emphasis is not therefore on technical issues, though these are brought into consideration where relevant, but on the soft, or human centred, issues associated with achieving user privacy.
2016 International Joint Conference on Neural Networks (IJCNN), 2016
Mechatronic Futures, 2016
Neural Computing and Applications, 2016
Jorge Azorin-Lopez et al. has been included to focus on validate the nD-SOM-PINT proposal in othe... more Jorge Azorin-Lopez et al. has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.
This research approaches a vision problem considering the adverse conditions of perception tasks.... more This research approaches a vision problem considering the adverse conditions of perception tasks. In particular, structural defects in specular surfaces, whatever is the form of these surfaces are characterized. The reflections and the brightness cause the characteristics of the objects usually measured by common vision systems (color, topography, form etc.) to be hidden in normal conditions. From the applied point of view, the work is centered on systems using automatic visual inspection of these surfaces. From the interest of the practical implantation, the requirements that they must fulfill habitually condition the solutions that could be proposed. In fact, each problem demands a new solution of technological design. The vision systems are oriented to applications.
A real time vision system of images perceived in real environments based on reconfigurable archit... more A real time vision system of images perceived in real environments based on reconfigurable architecture is presented. The system provides surface labelling of the input images of unstructured scenes, irrespective of the environmental lighting or scale conditions adapting the response to temporal restrictions. The nucleus of the system is based on querying self-organizing maps constructed with supervised training by means of descriptors extracted from images of different surfaces perceived for successive values of the optical parameters (lighting and scale). To improve the labelling process the system estimates the environmental optical parameters and then self-organizing maps are reconfigured. A segmented architecture is proposed for the central module of the labelling process, which will improve the performance of image sequences. A prototype implemented on FPGAs applied as a guidance aid for vehicles is provided. This prototype can regulate its processing frequency at the speed demanded by the vehicle.
Neural Computing and Applications, 2016
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Papers by Jorge Azorin-Lopez