(B) Instantaneous worm pose encoded as the centerline curve parameterized by tangent angles θ = ( θ 1, … θ i, … θ N) ordered from head to tail. (A) An exemplar collection of images displaying coiled shapes. elegans naturally exhibits a variety of coiled shapes which challenge the determination of the centerline posture, a fundamental component for quantitative behavioral understanding.
These shapes occur in important behaviors such as an escape response, among mutants and are a yet unanalyzed component in increasingly copious and quantitative recordings such as the Open Worm Movement Database. Even with a relatively simple body plan, identifying the centerline can be challenging due to coiling and other self-occluded shapes, Fig 1. ), provides an illustrative example, where “pose” can be identified as the geometry of the centerline extracted from worm images. elegans, important on its own as a model system (see e.g. Estimating and analyzing posture and posture sequences from high-resolution video data is thus a general and important problem, and the basis of a new quantitative approach to movement behavior (for reviews see e.g. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Īll animals, including humans, reveal important and subtle information about their internal dynamics in their outward configurations of body posture, whether these internal dynamics originate from gene expression, neural activity, or motor control strategies. įunding: We acknowledge funding from the Vrije Universiteit Amsterdam and OIST Graduate University. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: The data is available here. Received: OctoAccepted: MaPublished: April 27, 2021Ĭopyright: © 2021 Hebert et al. We expect that the combination of a body model and image synthesis demonstrated in WormPose will be both of general interest and important for future progress in precise pose estimation in other slender-bodied and deformable organisms.Ĭitation: Hebert L, Ahamed T, Costa AC, O’Shaughnessy L, Stephens GJ (2021) WormPose: Image synthesis and convolutional networks for pose estimation in C.
:origin()/pre00/2f3d/th/pre/f/2014/015/d/b/super_smash_flash_platform_wip_clock_town_by_birdman91-d72cl00.png "worms 2d info porject x")
We also show that incoherent body motions in the dwell state, which do not translate the worm, have been misidentified as an increase in reversal rate by previous, centroid-based methods. We apply WormPose to on-food recordings, finding a near absence of deep δ-turns.
WORMS 2D INFO PORJECT X GENERATOR
WormPose provides pose estimation that works across imaging conditions, naturally complements existing worm trackers, and harnesses the power of deep convolutional networks but with an image generator to automatically provide precise image-centerline pairings for training. elegans, exhibited in a variety of important natural contexts, is the primary limiting factor for fully automated high-throughput behavior analysis. Such animals also frequently coil, resulting in complicated shapes whose ambiguity presents difficulties for standard pose estimation methods.
WORMS 2D INFO PORJECT X MANUAL
Recent advances in machine learning have enabled the high-resolution estimation of bodypoint positions of freely behaving animals, but manual labeling can render these methods imprecise and impractical, especially in highly deformable animals such as the nematode C.
0 kommentar(er)
