Articles producció científica> Enginyeria Informàtica i Matemàtiques

A probabilistic integrated object recognition and tracking framework

  • Identification data

    Identifier: imarina:9285158
  • Authors:

    Serratosa F
    Alquézar R
    Amézquita N
  • Others:

    Author, as appears in the article.: Serratosa F; Alquézar R; Amézquita N
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Serratosa Casanelles, Francesc d'Assís
    Keywords: Visual tracking Video sequences Video recording System Probabilistic methods Performance evaluation People Occlusion Object tracking Object recognition Multiple Integration Image segmentation Features Feature extraction Dynamic environments Bayesian networks Appearance models
    Abstract: This paper describes a probabilistic integrated object recognition and tracking framework called PIORT, together with two specific methods derived from it, which are evaluated experimentally in several test video sequences. The first step in the proposed framework is a static recognition module that provides class probabilities for each pixel of the image from a set of local features. These probabilities are updated dynamically and supplied to a tracking decision module capable of handling full and partial occlusions. The two specific methods presented use RGB color features and differ in the classifier implemented: one is a Bayesian method based on maximum likelihood and the other one is based on a neural network. The experimental results obtained have shown that, on one hand, the neural net based approach performs similarly and sometimes better than the Bayesian approach when they are integrated within the tracking framework. And on the other hand, our PIORT methods have achieved better results when compared to other published tracking methods in video sequences taken with a moving camera and including full and partial occlusions of the tracked object. © 2011 Elsevier Ltd. All rights reserved.
    Thematic Areas: Química Operations research & management science Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General engineering Farmacia Engineering, electrical & electronic Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação Economia Direito Computer science, artificial intelligence Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Artificial intelligence Arquitetura, urbanismo e design Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: francesc.serratosa@urv.cat
    Author identifier: 0000-0001-6112-5913
    Record's date: 2023-02-19
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S0957417412001017
    Papper original source: Expert Systems With Applications. 39 (8): 7302-7318
    APA: Serratosa F; Alquézar R; Amézquita N (2012). A probabilistic integrated object recognition and tracking framework. Expert Systems With Applications, 39(8), 7302-7318. DOI: 10.1016/j.eswa.2012.01.088
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1016/j.eswa.2012.01.088
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2012
    Publication Type: Journal Publications
  • Keywords:

    Artificial Intelligence,Computer Science Applications,Computer Science, Artificial Intelligence,Engineering (Miscellaneous),Engineering, Electrical & Electronic,Operations Research & Management Science
    Visual tracking
    Video sequences
    Video recording
    System
    Probabilistic methods
    Performance evaluation
    People
    Occlusion
    Object tracking
    Object recognition
    Multiple
    Integration
    Image segmentation
    Features
    Feature extraction
    Dynamic environments
    Bayesian networks
    Appearance models
    Química
    Operations research & management science
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General engineering
    Farmacia
    Engineering, electrical & electronic
    Engineering (miscellaneous)
    Engineering (all)
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Enfermagem
    Educação
    Economia
    Direito
    Computer science, artificial intelligence
    Computer science applications
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
    Artificial intelligence
    Arquitetura, urbanismo e design
    Administração, ciências contábeis e turismo
    Administração pública e de empresas, ciências contábeis e turismo
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