Browsing NTNU Open by Author "Pinto, Allan"

Now showing items 1-15 of 15

    • Application-Oriented Retinal Image Models for Computer Vision 

      Silva, Ewerton; Torres, Ricardo Da Silva; Pinto, Allan; Li, Lin; Vianna, José; Azevedo, Rodolfo; Goldenstein, Siome (Peer reviewed; Journal article, 2020)
      Energy and storage restrictions are relevant variables that software applications should be concerned about when running in low-power environments. In particular, computer vision (CV) applications exemplify well that ...

    • Automatic Markerless Motion Detector Method against Traditional Digitisation for 3-Dimensional Movement Kinematic Analysis of Ball Kicking in Soccer Field Context 

      Palucci Vieira, Luiz H.; Santiago, Paulo R P; Pinto, Allan; Aquino, Rodrigo; Torres, Ricardo; Barbieri, Fabio A. (Peer reviewed; Journal article, 2022)
      Kicking is a fundamental skill in soccer that often contributes to match outcomes. Lower limb movement features (e.g., joint position and velocity) are determinants of kick performance. However, obtaining kicking kinematics ...

    • Characterization and analyses of dribbling actions in soccer: a novel definition and effectiveness of dribbles in the 2018 FIFA World Cup RussiaTM 

      Leal, Kleber; Pinto, Allan; Torres, Ricardo Da Silva; Elferink-Gemser, Marije; Cunha, Sergio (Peer reviewed; Journal article, 2022)
      Purpose Dribbling is a significant skill in soccer, owing to its effectiveness to create opportunities for scoring, and has been analysed from different perspectives, including the development of talented players. This ...

    • Classification and determinants of passing difficulty in soccer: a multivariate approach 

      Merlin, Murilo; Pinto, Allan; de Almeida, Alexandre Gomes; Moura, Felipe A; Torres, Ricardo Da Silva; Cunha, Sergio Augusto (Peer reviewed; Journal article, 2021)
      Introduction Usually, the players’ or teams’ efficiency to perform passes is measured in terms of accuracy. The degree of difficulty of this action has been overlooked in the literature. Objectives The present study ...

    • Litter Detection with Deep Learning: A Comparative Study 

      Cordova, Manuel; Pinto, Allan; Hellevik, Christina Carrozzo; Alaliyat, Saleh Abdel-Afou; Hameed, Ibrahim A.; Pedrini, Helio; Torres, Ricardo da S. (Peer reviewed; Journal article, 2022)
      Pollution in the form of litter in the natural environment is one of the great challenges of our times. Automated litter detection can help assess waste occurrences in the environment. Different machine learning solutions ...

    • Measuring Economic Activity From Space: A Case Study Using Flying Airplanes and COVID-19 

      Segundo, Mauricio; Pinto, Allan; Minetto, Rodrigo; Torres, Ricardo Da Silva; Sarkar, Sudeep (Peer reviewed; Journal article, 2021)
      This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas. We hypothesize that disturbances in human behavior caused by major life-changing events leave ...

    • MobText: A Compact Method for Scene Text Localization 

      Decker, Luis; Pinto, Allan; Campana, Jose; Neira, Manuel; Santos, Andreza; Conceição, Jhonatas; Angeloni, Marcus; Li, Lin; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2020)
      Abstract: Multiple research initiatives have been reported to yield highly effective results for the text detection problem. However, most of those solutions are very costly, which hamper their use in several applications ...

    • A Multirepresentational Fusion of Time Series for Pixelwise Classification 

      Dias, Danielle; Pinto, Allan; Dias, Ulisses; Lamparelli, Rubens; Le Maire, Guerric; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2020)
      This article addresses the pixelwise classification problem based on temporal profiles, which are encoded in 2-D representations based on recurrence plots, Gramian angular/ difference fields, and Markov transition field. ...

    • On the Fusion of Text Detection Results: A Genetic Programming Approach 

      Campana, Jose; Pinto, Allan; Neira, Manuel; Decker, Luis; Santos, Andreza; Conceição, Jhonatas; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2020)
      Hundreds of text detection methods have been proposed, motivated by their widespread use in several applications. Despite the huge progress in the area, which includes even the use of sophisticated learning schemes, ad-hoc ...

    • Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation 

      Pinto, Allan; Cordova, Manuel; Decker, Luis; Campana, Jose; Souza, Marcos; Andreza, Santos; Jhonatas, Conceição; Gagliardi, Henrique; Luvizon, Diogo; Torres, Ricardo Da Silva; Pedrini, Helio (Chapter, 2020)
      Stereo vision is a growing topic in computer vision due to the innumerable opportunities and applications this technology offers for the development of modern solutions, such as virtual and augmented reality applications. ...

    • Pelee-Text++: A Tiny Neural Network for Scene Text Detection 

      Cordova, Manuel; Pinto, Allan; Pedrini, Helio; Torres, Ricardo Da Silva (Journal article; Peer reviewed, 2020)
      Scene text detection has become an important field in the computer vision area due to the increasing number of applications. This is a very challenging problem as textual elements are commonly found in “noisy” and complex ...

    • The PlastOPol system for marine litter monitoring by citizen scientists 

      Wu, Di; Liu, Jincheng; Cordova, Manuel; Hellevik, Christina Carrozzo; Cyvin, Jakob Bonnevie; Pinto, Allan; Hameed, Ibrahim A.; Pedrini, Helio; Da Silva Torres, Ricardo; Fet, Annik Magerholm (Peer reviewed; Journal article, 2023)
      Marine plastic pollution has in recent decades become ubiquitous, posing threats to flora, fauna, and potentially human health. Proper monitoring and registration of litter occurrences are, therefore, of paramount importance ...

    • Sport action mining: Dribbling recognition in soccer 

      Barbon Junior, Sylvio; Pinto, Allan; Barroso, João Vitor; Caetano, Fabio Giuliano; Moura, Felipe Arruda; Cunha, Sergio Augusto; Torres, Ricardo Da Silva (Journal article; Peer reviewed, 2021)
      Recent advances in Computer Vision and Machine Learning empowered the use of image and positional data in several high-level analyses in Sports Science, such as player action classifcation, recognition of complex human ...

    • Toward characterizing cardiovascular fitness using machine learning based on unobtrusive data 

      Frade, Maria Cecília Moraes; Beltrame, Thomas; de Oliveira Gois, Mariana; Pinto, Allan; de Moura Tonello, Silvia Cristina Garcia; Da Silva Torres, Ricardo; Catai, Aparecida Maria (Peer reviewed; Journal article, 2023)
      Cardiopulmonary exercise testing (CPET) is a non-invasive approach to measure the maximum oxygen uptake (), which is an index to assess cardiovascular fitness (CF). However, CPET is not available to all populations and ...

    • Using machine learning pipeline to predict entry into the attack zone in football 

      Stival, Leandro; Pinto, Allan; Andrade, Felipe dos Santos Pinto de; Santiago, Paulo Roberto Pereira; Biermann, Henrik; Da Silva Torres, Ricardo; Dias, Ulisses (Peer reviewed; Journal article, 2023)
      Sports sciences are increasingly data-intensive nowadays since computational tools can extract information from large amounts of data and derive insights from athlete performances during the competition. This paper addresses ...