FCAI SIG

AI for computer vision

Coordination: Professor Moncef Gabbouj (University of Tampere), Professor Guoying Zhao (University of Oulu), Professor Juho Kannala (Aalto University)

One of the core computer vision areas, namely, object recognition with large scale image datasets, was accredited largely for the recent advances in machine learning especially deep learning. Object classification with deep learning and large scale data is arguably what reignited the field of artificial neural networks and triggered a revolution in artificial intelligence. Since then, deep learning techniques shine in a broad range of areas such as computer vision, speech recognition and language translation.

Nowadays, artificial intelligence has spread over almost all fields of science and technology. Yet, computer vision remains in the heart of these advances when it comes to visual data analysis, offering the biggest big data and enabling advanced AI solutions to be developed focusing on the various problems and applications of computer vision.

Computer vision research in Finland is distributed in many research organizations with a large concentration at the University of Oulu. FCAI SIG AI for computer vision (CVAI) coordinates research activities using and developing AI tools for computer vision under FCAI umbrella for more efficient cooperation and synergy between the research organizations in Finland.

Objectives

FCAI SIG AI for computer vision aims to bring together experts and research groups in different research organizations in Finland to exchange ideas and collaborate towards a more coordinated and efficient contributions to solving the main challenges in the field for the benefit of the research organizations, the industry and the society at large.

Activities

  • Organize some workshops and seminars to support collaboration among research groups and with industry; 

  • Share information regarding projects, funding, education, positions, etc; 

  • Researcher exchanges between CV groups

  • Activities with Pattern Recognition Society of Finland

  • More information on past and future SIG activities

Research themes

  • Fundamental feature representation

  • Visual information retrieval

  • Affective computing from visual analysis

  • 3D vision

  • Medical and biomedical image analysis

  • Autonomous systems

  • Learning in vision

  • Empathic building

  • Materials sciences

  • Industrial applications of CV

  • Bio-marine monitoring

  • Camera imaging

  • Remote sensing

  • Safely, security and privacy

Main challenges

The main challenges encountered in the field of AI for CV include 

  • Energy efficient algorithms

  • Edge computing solutions

  • Hardware accelerators

  • Algorithm–hardware codesign

  • Learning with less labels

  • Efficient feature representation for small scale and imbalanced data

People:

  • Liu Li, UO 

  • Janne Heikkilä, UO

  • Matti Pietikäinen, UO

  • Guoying Zhao, UO

  • Petri Myllymäki, UH

  • Paavo Nevalainen, UTU

  • Jukka Heikkonen, UTU

  • Esa Rahtu, TAU

  • Ville Kyrki, Aalto 

  • Hannu Karvonen, VTT

  • Otto Korkalo, VTT

  • Jani Boutellier, UV

  • Arto Klami, UH

  • Markus Koskela, CSC

  • Juho Kannala, Aalto

  • Patrik Floreen, UH

  • Jorma Laaksonen, Aalto 

  • Miguel Bordallo Lopez, VTT

  • Heikki Huttunen, TAU

  • Lasse Lensu, LUT

  • Heikki Kälviäinen, LUT

  • Pekka Pöyry, TAMK