IEEE Computational Intelligence Society
Task Force on Evolutionary Computer Vision and Image Processing

Motivation

Vision is the complex process of deriving meaning from what is seen. The fields of computer vision and image processing have tried to automate tasks that the human visual system can do, with the aim of gaining a high-level understanding of images and videos. Computer vision algorithms have been successfully applied to a high number of real-world problems ranging from remote sensing to medical image analysis, video surveillance, human-robot interaction, and computer-aided design. In turn, evolutionary computation methods have been shown to be more efficient than classical optimization approaches for discontinuous, non-differentiable, multimodal and noisy problems. They have also demonstrated their ability as robust approaches to cope with the fundamental steps of the computer vision and image processing pipeline (e.g. restoration, segmentation, registration, or tracking). As a result of the convergence of the computer vision and evolutionary computation research fields, a large number of research activities have arisen in the last two decades including a myriad of scientific papers, international projects, book chapters, special sessions in conferences, and special issues in journals.

Taken into account the aforementioned context, the ECVIP task force (TF) was born in 2010 as a common track to relate all events bringing together evolutionary computation and computer vision. The main idea was to convert this TF in an outstanding tool able to create a coordinated body to interconnect all kinds of activities that, prior to the existence and consolidation of the TF, were generally announced in isolation. Individual conferences and other kinds of specific activities only provide limited means to open a fruitful exchange of ideas, transfer of tools, and generation of new research lines, while our objectives require a supervised and integrated series of actions with the continuous participation of recognized researchers. The ECVIP TF provides not only excellent opportunities to organize activities, especially but not exclusively in the framework of IEEE journals and IEEE supported conferences, but also to define the research agenda for the future in advanced evolutionary algorithms in computer vision and image processing.

Goals and Scope

Goals

The main goal of this TF is to promote research on evolutionary computer vision and image processing, facilitating the knowledge transfer and collaboration between researchers from different disciplines (e.g. evolutionary computation, computer vision, deep learning, biomedical imaging, signal processing, pattern recognition).

The main goal of this TF can be divided in the following sub-objectives:

  • strengthen an active community to promote the TF areas of interest
  • encourage and facilitate the collaboration and dialogue between different scientific communities
  • make students, teachers, researchers, developers, and end-users aware of the state-of-the-art
  • foster the use of computational intelligence-based methodologies/techniques in computer vision and image processing
  • organize conferences, tutorials, workshops and special sessions
  • launch edited volumes, books, and special issues in journals

Scope

This task force is focused on all aspects (theory, practice and applications) belonging to the intersection between evolutionary computation/computational intelligence and disciplines like computer vision, image processing, medical imaging, deep learning, signal processing and pattern recognition.

Topics of interest include but are not limited to:

  • Evolutionary Computer Vision
  • Evolutionary Image Processing and Analysis
  • Evolutionary Image Understanding
  • Evolutionary Medical Imaging
  • Evolutionary Computation in Deep Learning
  • Evolutionary Models of Vision and Cognition
  • Computational Intelligence in Computer Vision
  • Computational Intelligence in Image Processing and Analysis
  • Computational Intelligence in Signal Processing
  • Computational Intelligence in Pattern Recognition

Activities

Coming Activities

    • IEEE WCCI: Special Session on Evolutionary Computer Vision and Image ProcessingLink
    • IEEE SSCI: IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision ProcessingLink
    • IEEE SSCI: Special Session on Evolutionary Computation for Computer Vision and Image AnalysisLink
    • GECCO 2022: Special session on Evolutionary Computation for Explainable AI
    • GECCO 2022: Tutorial on Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern RecognitionLink
    • EvoConference: EvoApps 2022, Image & Signal Processing, Vision & Pattern Recognition
    • IDEAL: Special Session on Computational Intelligence for Computer Vision and Image ProcessingLink
    • Special Issue on Evolutionary and Memetic Algorithms for Computer Vision and Image Processing in the journal of Memetic Computing, 2021-2022
    • Special issue on Explainable Deep Learning for Medical Image Processing and Analysis (IEEE Transactions on Emerging Topics in Computational Intelligence)
    • Special Issue on Evolutionary Computer Vision (IEEE Transactions on Evolutionary Computation)
    • Special issue on Evolutionary Deep Learning for Computer Vision and Image Processing (Applied Soft Computing)Link
    • ICTS4eHealth 2022: IEEE Conference on ICT Solutions for eHealthLink

Past Activities

  • 2021

    • IEEE CEC: Special Session on Evolutionary Computer Vision and Image ProcessingLink
    • GECCO: Workshop on Medical Applications of Genetic and Evolutionary Computation 
    • GECCO: Tutorial on Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern Recognition
    • Evo* (EvoApps): Image & Signal Processing, Vision & Pattern RecognitionLink
    • IEEE SSCI: IEEE Symposium on Computational Intelligence in Feature Analysis, Selection and Learning in Image and Pattern Recognition
    • IEEE SSCI: IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision ProcessingLink
    • IEEE SSCI: Special Session Evolutionary Computation for Computer Vision and Image AnalysisLink
    • Authored book: Genetic Programming for Image Classification: An Automated Approach to Feature Learning, SpringerLink
  • 2020

    • ISVC: 15th International Symposium on Visual Computing (2020). Tutorial on Evolutionary Computer VisionLink
    • Special Issue on Evolutionary Neural Architecture Search and Applications, IEEE Computational Intelligence MagazineLink
    • Special Issue "Computer-aided Biomedical Imaging, Applied Sciences JournalLink
    • IEEE SSCI: IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision ProcessingLink
    • IEEE SSCI: IEEE Symposium on Computational Intelligence in Feature Analysis, Selection and Learning in Image and Pattern RecognitionLink
    • IEEE CEC: Special Session on Evolutionary Computer Vision and Image ProcessingLink
    • GECCO: Workshop on Medical Applications of Genetic and Evolutionary ComputationLink
    • GECCO: Tutorial on Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern RecognitionLink
    • GECCO: Tutorial on Evolutionary Computation for Feature Selection and Feature ConstructionLink
    • GECCO: Tutorial on Evolutionary Computer VisionLink
    • GECCO: Tutorial on Semantic Genetic ProgrammingLink
    • GECCO: Tutorial on Solving Complex Problems with Coevolutionary AlgorithmsLink
  • 2019

    • IEEE SSCI: IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition (IEEE FASLIP) at SSCI 2019, Xiamen, China
    • GECCO: Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC) 2019, as part of GECCO'19, 13-17 July 2019, Prague, Czech RepublicLink
    • IEEE CEC: Special Session on Evolutionary Computer Vision and Image Processing, 10-13 June 2019, Wellington, New ZealandLink
    • 22nd International Conference on the Applications of Evolutionary Computation (EvoApps 2019). Thematic Area: Image & Signal Processing, Vision & Pattern recognition. Leipzig, Germany. 24-26 April 2019Link
  • 2018

    • IEEE SSCI: IEEE Symposium on Computational Intelligence in Feature Analysis, Selection and Learning in Image and Pattern Recognition (FASLIP) 2018, 18-21 November, Bengaluru, India
    • GECCO: Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC) 2018, as part of GECCO'18, 15-19 July, Kyoto, Japan
    • IEEE CEC: Special Session on Evolutionary Computer Vision (CEC-9) 2018, as part of the IEEE WCCI'18, 8-13 July, Rio de Janeiro, Brazil
    • Evo* (EvoApps): Evolutionary Computation in Image Analysis, Signal Processing and Pattern RecognitionLink
    • Special Issue on Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. Algorithms 11(3): 25 (2018).Link
  • 2017

    • Special Issue on Evolutionary Computer Vision, Image Processing and Pattern Recognition. Applied Soft Computing. 2017

People

Harith Al-Sahaf

Chair

Victoria University of Wellington
New Zealand

Pablo Mesejo

Vice-Chair

University of Granada
Spain

Ying Bi

Vice-Chair

Victoria University of Wellington
New Zealand

Chair History

  • 2017-2021

    Pablo Mesejo

    University of Granada
    Spain

  • 2010-2017

    Sergio Damas

    European Center for Soft Computing
    Spain

Members

  • Lucia Ballerini (University of Edinburgh, UK)Link
  • Leonardo Bocchi (University of Florence, Italy)Link
  • Stefano Cagnoni (University of Parma, Italy)Link
  • Óscar Cordón (University of Granada, Spain)Link
  • Sergio Damas (University of Granada, Spain)Link
  • Eli David (Bar-Ilan University, Israel)Link
  • Ivanoe De Falco (ICAR-CNR, Italy)Link
  • Antonio Della Cioppa (University of Salerno, Italy)Link
  • Francesco Fontanella (University of Cassino and Southern Lazio, Italy)Link
  • Florence Forbes (Inria, France)Link
  • Óscar Ibáñez (University of Granada/Panacea Cooperative Research, Spain)Link
  • Chia-Feng Juang (National Chung Hsing University, Taiwan)Link
  • Mario Köppen (Kyushu Institute of Technology, Japan)Link
  • Krzysztof Krawiec (Poznan University of Technology, Poland)Link
  • Evelyne Lutton (INRA, France)Link
  • Sushmita Mitra (Indian Statistical Institute, India)Link
  • Amir Nakib (University of Paris-Est, France)Link
  • Youssef S. G. Nashed (Argonne National Laboratory, USA)Link
  • Jorge Novo (University of A Coruña, Spain)Link
  • Gustavo Olague (CICESE, Mexico)Link
  • Marcos Ortega (University of A Coruña, Spain)Link
  • Clara Pizzuti (ICAR-CNR, Italy)Link
  • Riccardo Poli (University of Essex, UK)Link
  • Kai Qin (Swinburne University of Technology, Australia)Link
  • Alessandra Scotto di Freca (University of Cassino and Southern Lazio, Italy)Link
  • Stephen L. Smith (University of York, UK)Link
  • Andy Song (RMIT University, Australia)Link
  • Yanan Sun (Sichuan University, China)Link
  • Siham Tabik (University of Granada, Spain)Link
  • Bing Xue (Victoria University of Wellington, New Zealand)Link
  • Mengjie Zhang (Victoria University of Wellington, New Zealand)Link
  • Jacek M. Zurada (University of Louisville, USA)Link
  • Qurrat Ul Ain (Victoria University of Wellington, New Zealand)Link