Percorrer por autor "Costa, Paulo"
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- Correction to: A review of assistive spatial orientation and navigation technologies for the visually impairedPublication . Fernandes, Hugo; Costa, Paulo; Filipe, Vitor; Paredes, Hugo; Barroso, JoãoThe fourth author name was missed in the original publication. The correct list of authors should read as “Hugo Fernandes, Paulo Costa, Vitor Filipe, Hugo Paredes, João Barroso”. It has been corrected in this erratum. The original article has been updated.
- Fiducials Marks Detection to Assist Visually Impaired People NavigationPublication . Costa, Paulo; Fernandes, Hugo; Vasconcelos, Veronica; Coelho, Paulo; Barroso, Joao; Hadjileontiadis, LeontiosAssistive technology enables people to achieve independence in the accomplishment of their daily tasks and enhance their quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of information or given unsufficient information about their surrounding environment. With the recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities during their mobility. In this context we propose and describe the SmartVision project, whose global objective is to assist visually impaired people in their navigation through unknown indoor and outdoor environments. This paper is focused mainly on the Computer Vision module of the SmartVision prototype, were we propose a new algorithm to recognise fiducials marks suitably placed on sidewalks, revealing to be a promising solution.
- Landmarks Detection to Assist the Navigation of Visually Impaired PeoplePublication . Costa, Paulo; Fernandes, Hugo; Vasconcelos, Verónica; Coelho, Paulo; Barroso, João; Hadjileontiadis, LeontiosAssistive technology enables people to achieve independence in the accomplishment of their daily tasks and enhance their quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of information or given insufficient information about their surrounding environment. With the recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities during their mobility. In this context we propose a new algorithm to recognize landmarks suitably placed on sidewalks. The proposed algorithm uses a combination of Peano-Hilbert Space Filling Curves for dimension reduction of image data and Ensemble Empirical Mode Decomposition (EEMD) to pre-process the image, resulting on a fast and efficient recognition method and revealing a promising solution.
- Lipid composition and nutritional quality of intramuscular fat in Charneca-PDO beefPublication . Pestana, José M; Costa, Ana S. H.; Alfaia, Cristina M.; Costa, Paulo; Martins, Susana V.; Alves, Susana P.; Bessa, Rui J. B.; Prates, José A. M.This paper characterizes the intramuscular fat from longissimus lumborum (LL, relatively red) and semitendinous (ST, relatively white) muscles of Charneca beef from young bulls reared according to the protected designation of origin (PDO) specifications. The content of total lipids, total cholesterol, α-tocopherol and β-carotene, as well as the fatty acid composition, including the isomeric distribution of conjugated linoleic acid (CLA), was assessed. Charneca young bulls (n = 10) were raised on a semi-extensive production system, in which animals fed pasture plus concentrate during 15 months. The ST muscle was leaner and had higher percentages of PUFA, in contrast to the LL muscle, which presented higher percentages of SFA and MUFA. Thus, the ST muscle had a higher PUFA/SFA ratio than the LL muscle, although the ratio values of both muscles were inside the recommended figures for the human diet. In contrast, the contents of CLA isomers, total cholesterol, α-tocopherol and β-carotene, as well as the n-6/n-3 ratio, were not influenced by muscle type, thus suggesting no carcass variation for these compounds. In both muscles, the n-6/n-3 ratios were slightly above the dietary guideline for human diet, and the contents of α-tocopherol were very high, indicating a good lipid stability of Charneca-PDO beef. Overall, the results suggest that intramuscular fat of Charneca-PDO beef has good human health-related parameters, with small carcass variation, since the PUFA/SFA and n-6/n-3 ratio values are inside or very close to the recommended figures for the human diet, and the content of α-tocopherol is very high.
- Obstacle detection and avoidance module for the blindPublication . Costa, Paulo; Fernandes, Hugo; Barroso, João; Paredes, Hugo; Hadjileontiadis, Leontios J.; CostaAssistive technology enables people to achieve independence when performing daily tasks and it enhances their overall quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of sufficient information about their surrounding environment. With recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities in terms of their mobility. In this context we present and describe a wearable system (Blavigator project), whose global objective is to assist visually impaired people in their navigation on indoor and outdoor environments. This paper is focused mainly on the Computer Vision module of the Blavigator prototype. We propose an object collision detection algorithm based on stereo vision. The proposed algorithm uses Peano-Hilbert Ensemble Empirical Mode Decomposition (PH-EEMD) for disparity image processing and a two layer disparity image segmentation to detect nearby objects. Using the adaptive ensemble empirical mode decomposition (EEMD) image analysis real time is not achieved, with PH-EEMD results on a fast implementation suitable for real time applications.
- Obstacle Detection using Stereo Imaging to Assist the Navigation of Visually Impaired PeoplePublication . Costa, Paulo; Fernandes, Hugo; Martins, Paulo; Barroso, João; Hadjileontiadis, Leontios J.Assistive technology enables people to achieve independence when performing daily tasks and it enhances their overall quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of sufficient information about their surrounding environment. With recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities in terms of their mobility. In this context we propose and describe the Blavigator project, whose global objective is to assist visually impaired people in their navigation on indoor and outdoor environments. This paper is focused mainly on the Computer Vision module of the Blavigator prototype. We propose an object collision detection algorithm based on disparity images. The proposed algorithm uses a 2D Ensemble Empirical Mode Decomposition image optimization algorithm and a two layer disparity image segmentation to detect nearby objects.
- Prototype to Increase Crosswalk Safety by Integrating Computer Vision with ITS-G5 TechnologiesPublication . Gaspar, Francisco; Guerreiro, Vitor; Loureiro, Paulo; Costa, Paulo; Mendes, Sílvio; Rabadão, CarlosHuman errors are probably the main cause of car accidents, and this type of vehicle is one of the most dangerous forms of transport for people. The danger comes from the fact that on public roads there are simultaneously different types of actors (drivers, pedestrians or cyclists) and many objects that change their position over time, making difficult to predict their immediate movements. The intelligent transport system (ITS-G5) standard specifies the European communication technologies and protocols to assist public road users, providing them with relevant information. The scientific community is developing ITS-G5 applications for various purposes, among which is the increasing of pedestrian safety. This paper describes the developed work to implement an ITS-G5 prototype that aims at the increasing of pedestrian and driver safety in the vicinity of a pedestrian crosswalk by sending ITS-G5 decentralized environmental notification messages (DENM) to the vehicles. These messages are analyzed, and if they are relevant, they are presented to the driver through a car’s onboard infotainment system. This alert allows the driver to take safety precautions to prevent accidents. The implemented prototype was tested in a controlled environment pedestrian crosswalk. The results showed the capacity of the prototype for detecting pedestrians, suitable message sending, the reception and processing on a vehicle onboard unit (OBU) module and its presentation on the car onboard infotainment system.
- Synthetic image generation for effective deep learning model training for ceramic industry applicationsPublication . Gaspar, Fábio; Daniel Carreira; Rodrigues, Nuno; Miragaia, Rolando; Costa, Paulo; Pereira, António; Ribeiro, JoséIn the rapidly evolving field of machine learning engineering, access to large, high-quality, and well-balanced labeled datasets is indispensable for accurate product classification. This necessity holds particular significance in sectors such as the ceramics industry, in which effective production line activities are paramount and deep learning classification mechanisms are particularly relevant for streamlining processes; but real-world image samples are scarce and difficult to obtain, hindering dataset building and consequently model training and deployment. This paper presents a novel approach for dataset building in the context of the ceramic industry, which involves employing synthetic images for building or complementing datasets for image classification problems. The proposed methodology was implemented in CeramicFlow, an innovative computer graphics rendering pipeline designed to create synthetic images by employing computer-aided design models of ceramic objects and incorporating domain randomization techniques. As a result, a fully synthetic image dataset named Synthetic CeramicNet was created and validated in real-world ceramic classification problems. The results demonstrate that synthetic images provide an adequate basis for datasets and can significantly reduce reliance on real-world data when developing deep learning approaches for image classification problems in the ceramic industry. Furthermore, the proposed approach can potentially be applied to other industrial fields.
- Using Peano–Hilbert space filling curves for fast bidimensional ensemble EMD realizationPublication . Costa, Paulo; Barroso, João; Fernandes, Hugo; Hadjileontiadis, Leontios JEmpirical mode decomposition (EMD) is a fully unsupervised and data-driven approach to the class of nonlinear and non-stationary signals. A new approach is proposed, namely PHEEMD, to image analysis by using Peano–Hilbert space filling curves to transform 2D data (image) into 1D data, followed by ensemble EMD (EEMD) analysis, i.e., a more robust realization of EMD based on white noise excitation. Tests’ results have shown that PHEEMD exhibits a substantially reduced computational cost compared to other 2D-EMD approaches, preserving, simultaneously, the information lying at the EMD domain; hence, new perspectives for its use in low computational power devices, like portable applications, are feasible.