[image 04451] IJCV Special Issue on Computer Vision Approach for Animal Tracking and Modeling

[Shohei Nobuhara]

ImageMLの皆さま

京都大学の延原と申します．下記の通り，論文誌International Journal of Computer
Visionにて特集号「Special Issue on Computer Vision Approach for Animal
Tracking and Modeling」の論文募集を行っております．

投稿締め切りは2022年3月27日です．詳しくは

　https://www.springer.com/journal/11263/updates/19611514

をご確認ください．皆様からのご投稿お待ちしております．
よろしくお願いいたします．

====================================================
Call for Papers: Special Issue on Computer Vision Approach for Animal
Tracking and Modeling

Guest Editors

  Hyun Soo Park; University of Minnesota
  Helge Rhodin; University of British Columbia
  Angjoo Kanazawa; University of California, Berkeley
  Natalia Neverova; Facebook AI Research
  Shohei Nobuhara; Kyoto University
  Michael Black; Max Planck Institute for Intelligent Systems


Many biological organisms are evolved to exhibit diverse
quintessential behaviors via physical and social interactions with
surroundings, and understanding these behaviors is a fundamental goal
of multiple disciplines including neuroscience, biology, animal
husbandry, ecology, and animal conservation. For example, ethogramming
characterizes the behavioral states and their transitions, which
further provides a scientific basis to understand innate human
behaviors, e.g., decision making, attention, and group behaviors.
These analyses require objective, repeatable, and scalable
measurements of animal behaviors that are not possible with existing
methodologies that leverage manual encoding from animal experts and
specialists. Recently, computer vision has been making a
groundbreaking impact by providing a new tool that enables
computational measurements of the behaviors.

Despite its significance, the area of animal tracking and modeling is
still under-explored and under-represented in computer vision,
compared to that of human subjects. While computer vision methods to
track, model, and reconstruct humans are highly inspirational, we
argue that these methods are not necessarily applicable to a new
animal species without non-trivial modifications. This performance
degradation stems from various reasons including scarce annotated
data, characteristic body movements and constraints (e.g., bipedal vs.
quadrupedal vs. polypedal), irregular/homogeneous skin texture, and
limited resolution due to remote sensing. This requires a series of
innovations.

This special issue is motivated by the amount of enthusiasm (more than
50 paper submissions and 120 attendances) seen at our CVPR 2021
workshop on CV4Animals: Computer Vision for Animal Tracking and
Modeling, which showcased interdisciplinary demands and interests in
the topic. However, there exists no formal publication venue to
consolidate this newly emerging field. We, therefore, propose this
special issue, aiming to address this.


Aims and Scope

  Animal motion capture and data
    Marker/markerless capture
    Camera trap remote capture
    Underwater capture
    Neuro-motor data recording

  Animal behavior tracking
    Fine-grain detection/segmentation/categorization of animals and
their species
    2D/3D pose/shape estimation
    Skin texture reconstruction
    Deformable body modeling
    Counting
    Re-Identification

  Animal behavior modeling
    Behavioral state characterization/classification (ethogramming)
    Dynamics of group/herd/flock behavior
    Behavior analysis and prediction
    Neuro-motor relation learning
    Behavior assessment


Important Dates

  Full paper submission deadline: March 27, 2022
  Review deadline: June 18, 2022
  Author response deadline: July 22, 2022
  Final notification: September 23, 2022
  Final manuscript submission: October 28, 2022
====================================================

-- 
  Shohei Nobuhara <nob ＠ i.kyoto-u.ac.jp>