DeepWild: Application of the pose estimation tool DeepLabCut for behaviour tracking in wild chimpanzees and bonobos

被引:11
|
作者
Wiltshire, Charlotte [1 ]
Lewis-Cheetham, James [1 ]
Komedova, Viola [1 ]
Matsuzawa, Tetsuro [2 ,3 ]
Graham, Kirsty E. [1 ]
Hobaiter, Catherine [1 ]
机构
[1] Univ St Andrews, Sch Psychol & Neurosci, Wild Minds Lab, St Andrews, Scotland
[2] Chubu Gakuin Univ, Dept Pedag, Gifu, Japan
[3] CALTECH, Div Humanities & Social Sci, Pasadena, CA USA
基金
欧盟地平线“2020”;
关键词
artificial intelligence; automation; behaviour; deep learning; machine learning; primate; IMAGE-ANALYSIS; GAIT ANALYSIS; PAN-PANISCUS; HABITAT USE; NETWORKS; MODEL;
D O I
10.1111/1365-2656.13932
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
1. Studying animal behaviour allows us to understand how different species and individuals navigate their physical and social worlds. Video coding of behaviour is considered a gold standard: allowing researchers to extract rich nuanced behavioural datasets, validate their reliability, and for research to be replicated. However, in practice, videos are only useful if data can be efficiently extracted. Manually locating relevant footage in 10,000 s of hours is extremely time-consuming, as is the manual coding of animal behaviour, which requires extensive training to achieve reliability.2. Machine learning approaches are used to automate the recognition of patterns within data, considerably reducing the time taken to extract data and improving reliability. However, tracking visual information to recognise nuanced behaviour is a challenging problem and, to date, the tracking and pose-estimation tools used to detect behaviour are typically applied where the visual environment is highly controlled.3. Animal behaviour researchers are interested in applying these tools to the study of wild animals, but it is not clear to what extent doing so is currently possible, or which tools are most suited to particular problems. To address this gap in knowledge, we describe the new tools available in this rapidly evolving landscape, suggest guidance for tool selection, provide a worked demonstration of the use of machine learning to track movement in video data of wild apes, and make our base models available for use.4. We use a pose-estimation tool, DeepLabCut, to demonstrate successful training of two pilot models of an extremely challenging pose estimate and tracking problem: multi-animal wild forest-living chimpanzees and bonobos across behavioural contexts from hand -held video footage.5. With DeepWild we show that, without requiring specific expertise in machine learning, pose estimation and movement tracking of free-living wild primates in visually complex environments is an attainable goal for behavioural researchers.
引用
收藏
页码:1560 / 1574
页数:15
相关论文
共 19 条
  • [1] Multi-animal pose estimation, identification and tracking with DeepLabCut
    Jessy Lauer
    Mu Zhou
    Shaokai Ye
    William Menegas
    Steffen Schneider
    Tanmay Nath
    Mohammed Mostafizur Rahman
    Valentina Di Santo
    Daniel Soberanes
    Guoping Feng
    Venkatesh N. Murthy
    George Lauder
    Catherine Dulac
    Mackenzie Weygandt Mathis
    Alexander Mathis
    [J]. Nature Methods, 2022, 19 : 496 - 504
  • [2] Multi-animal pose estimation, identification and tracking with DeepLabCut
    Lauer, Jessy
    Zhou, Mu
    Ye, Shaokai
    Menegas, William
    Schneider, Steffen
    Nath, Tanmay
    Rahman, Mohammed Mostafizur
    Di Santo, Valentina
    Soberanes, Daniel
    Feng, Guoping
    Murthy, Venkatesh N.
    Lauder, George
    Dulac, Catherine
    Mathis, Mackenzie Weygandt
    Mathis, Alexander
    [J]. NATURE METHODS, 2022, 19 (04) : 496 - 504
  • [3] Surgical Tool Tracking and Pose Estimation in Retinal Microsurgery
    Rieke, Nicola
    Tan, David Joseph
    Alsheakhali, Mohamed
    Tombari, Federico
    di San Filippo, Chiara Amat
    Belagiannis, Vasileios
    Eslami, Abouzar
    Navab, Nassir
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2015, PT I, 2015, 9349 : 266 - 273
  • [4] Spontaneous reoccurrence of "scooping'', a wild tool-use behaviour, in naive chimpanzees
    Bandini, Elisa
    Tennie, Claudio
    [J]. PEERJ, 2017, 5
  • [5] Sex Differences in Object Manipulation in Wild Immature Chimpanzees (Pan troglodytes schweinfurthii) and Bonobos (Pan paniscus): Preparation for Tool Use?
    Koops, Kathelijne
    Furuichi, Takeshi
    Hashimoto, Chie
    van Schaik, Carel P.
    [J]. PLOS ONE, 2015, 10 (10):
  • [6] VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild
    Zhang, Yifu
    Wang, Chunyu
    Wang, Xinggang
    Liu, Wenyu
    Zeng, Wenjun
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 45 (02) : 2613 - 2626
  • [7] PARTIAL DISK TRACKING USING VISUAL SNAKES: APPLICATION TO SPACECRAFT POSE ESTIMATION
    Chakravarty, Rajtilok
    Schaub, Hanspeter
    [J]. SPACEFLIGHT MECHANICS 2009, VOL 134, PTS I-III, 2009, 134 : 359 - 377
  • [8] Real-time surgical tool tracking and pose estimation using a hybrid cylindrical marker
    Lin Zhang
    Menglong Ye
    Po-Ling Chan
    Guang-Zhong Yang
    [J]. International Journal of Computer Assisted Radiology and Surgery, 2017, 12 : 921 - 930
  • [9] Real-time surgical tool tracking and pose estimation using a hybrid cylindrical marker
    Zhang, Lin
    Ye, Menglong
    Chan, Po-Ling
    Yang, Guang-Zhong
    [J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2017, 12 (06) : 921 - 930
  • [10] User's Gaze Tracking System and Its Application using Head Pose Estimation
    Kim, Hyunduk
    Sohn, Myoung-Kyu
    Kim, Dong-Ju
    Ryu, Nuri
    [J]. 2014 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, MODELLING AND SIMULATION, 2014, : 166 - 171