Show simple item record Lonhus, Kirill Štys, Dalibor Saberioon, Mohammadmehdi Rychtáriková, Renata 2019-08-13T16:34:03Z 2019-08-13T16:34:03Z 2019-07-03
dc.identifier doi:10.5061/dryad.1j29991
dc.identifier.citation Lonhus K, Štys D, Saberioon M, Rychtáriková R (2019) Segmentation of laterally symmetric overlapping objects: application to images of collective animal behavior. Symmetry 11(7): 866.
dc.description Video analysis is currently the main non-intrusive method for the study of collective behavior. However, 3D-to-2D projection leads to overlapping of observed objects. The situation is further complicated by the absence of stall shapes for the majority of living objects. Fortunately, living objects often possess a certain symmetry which was used as a basis for morphological fingerprinting. This technique allowed us to record forms of symmetrical objects in a pose-invariant way. When combined with image skeletonization, this gives a robust, nonlinear, optimization-free, and fast method for detection of overlapping objects, even without any rigid pattern. This novel method was verified on fish (European bass, Dicentrarchus labrax, and tiger barbs, Puntius tetrazona) swimming in a reasonably small tank, which forced them to exhibit a large variety of shapes. Compared with manual detection, the correct number of objects was determined for up to almost 90% of overlaps, and the mean Dice-Sørensen coefficient was around 0.83. This implies that this method is feasible in real-life applications such as toxicity testing.
dc.relation.haspart doi:10.5061/dryad.1j29991/3
dc.relation.isreferencedby doi:10.3390/sym11070866
dc.subject biophysics
dc.subject image processing
dc.subject biometrics
dc.subject computer science
dc.title Data from: Segmentation of laterally symmetric overlapping objects: application to images of collective animal behavior
dc.type Article
dwc.ScientificName Dicentrarchus labrax
dwc.ScientificName Puntius tetrazona
dc.contributor.correspondingAuthor Lonhus, Kirill
prism.publicationName Symmetry

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Title Segmentation of Laterally Symmetric Overlapping Objects: Application to Images of Collective Animal Behaviour
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