Literature DB >> 34306605

GRAPHITE: A Graphical Environment for Scalable in situ Video Tracking of Moving Insects.

B J Rossetti1, T Dynes2, B Brosi3, J C de Roode2, J Kong1.   

Abstract

1. Methods for measuring animal movement are critical for understanding numerous ecological and evolutionary processes. However, few methods are available for small organisms, and even fewer methods offer consistent individual-level resolution while remaining affordable, scalable and operable in the field. 2. We describe a low-cost animal movement tracking method with a user-friendly graphical interface, called GRAPHITE. Our automated software can quantify motions of insects by offline video analysis of inexpensive and lightweight human-readable tags attached to individual insects. The integrated graphical editor provides a full-featured environment for users to review the generated tracking data and make individual- or group-level edits. 3. GRAPHITE is a novel video analysis and graphical editing software (MATLAB v.9.0.0+) that identifies tags in image frames with a minimal false negative rate, links sequences of corresponding tags into "tracks" for each individual insect, infers the tag identifier, and provides a user-friendly graphical environment for editing tracking data. Users can either batch process raw video data using the full analysis pipeline or execute GRAPHITE modules independently for a tailored analysis. 4. We demonstrate the efficacy of the developed software with a specific application to the movement of honey bees at the entrance of hives. However, this system can be easily modified to track individually marked insects of 3 mm and larger. A notable advantage of this method is its ability to provide easy access to individual-level tracking data using human-readable tags.

Entities:  

Keywords:  bees; computer vision; monitoring; tagging; tracking; video analysis

Year:  2017        PMID: 34306605      PMCID: PMC8302204          DOI: 10.1111/2041-210x.12944

Source DB:  PubMed          Journal:  Methods Ecol Evol            Impact factor:   7.781


  16 in total

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Authors:  W Daniel Kissling; David E Pattemore; Melanie Hagen
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Authors:  Danielle P Mersch; Alessandro Crespi; Laurent Keller
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Review 6.  Automated image-based tracking and its application in ecology.

Authors:  Anthony I Dell; John A Bender; Kristin Branson; Iain D Couzin; Gonzalo G de Polavieja; Lucas P J J Noldus; Alfonso Pérez-Escudero; Pietro Perona; Andrew D Straw; Martin Wikelski; Ulrich Brose
Journal:  Trends Ecol Evol       Date:  2014-06-05       Impact factor: 17.712

7.  idTracker: tracking individuals in a group by automatic identification of unmarked animals.

Authors:  Alfonso Pérez-Escudero; Julián Vicente-Page; Robert C Hinz; Sara Arganda; Gonzalo G de Polavieja
Journal:  Nat Methods       Date:  2014-06-01       Impact factor: 28.547

8.  Lightweight GPS-tags, one giant leap for wildlife tracking? An assessment approach.

Authors:  Mariano R Recio; Renaud Mathieu; Paul Denys; Pascal Sirguey; Philip J Seddon
Journal:  PLoS One       Date:  2011-12-07       Impact factor: 3.240

9.  Superspreading and the effect of individual variation on disease emergence.

Authors:  J O Lloyd-Smith; S J Schreiber; P E Kopp; W M Getz
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10.  How human location-specific contact patterns impact spatial transmission between populations?

Authors:  Lin Wang; Zhen Wang; Yan Zhang; Xiang Li
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

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  1 in total

1.  Bayesian Multi-Targets Strategy to Track Apis mellifera Movements at Colony Level.

Authors:  Jordão N Oliveira; Jônatas C Santos; Luis O Viteri Jumbo; Carlos H S Almeida; Pedro F S Toledo; Sarah M Rezende; Khalid Haddi; Weyder C Santana; Michel Bessani; Jorge A Achcar; Eugenio E Oliveira; Carlos D Maciel
Journal:  Insects       Date:  2022-02-09       Impact factor: 2.769

  1 in total

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