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Comparing accuracy of fish sperm motility measurements obtained from two computational extremes in tracking approaches: Nearest neighbor and multiple hypothesis tracking
Author(s) -
Neumann Giovano,
Joaquim Bernardes Junior Jurandir,
Neumann Valdecir,
Bombardelli Robie Allan
Publication year - 2021
Publication title -
reproduction in domestic animals
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.546
H-Index - 66
eISSN - 1439-0531
pISSN - 0936-6768
DOI - 10.1111/rda.13922
Subject(s) - sperm , tracking (education) , sperm motility , motility , bittorrent tracker , biology , computer science , artificial intelligence , computer vision , statistics , mathematics , eye tracking , genetics , psychology , pedagogy
We conducted a study to assess the accuracy of nearest neighbour (NN) and multiple hypothesis tracking (MHT) methods—which are opposite extremes in computational complexity—in determining the percentage of motile sperms and the number of sperms tracked in simulated data of fish sperm movements, and to evaluate the resulting number of tracking errors and analysis duration. Sperm tracking and swimming path assembly were assessed in 36 video clips (1 s length at 100 fps) of emulated Rhamdia quelen sperm kinetics at different densities (50, 100, 200 or 300 spermatozoa in the field of view) and motility rates (30, 60 or 90%). The MHT method accurately estimated the percentage of motile sperms, whereas NN underestimated it by up to 6.59%. Increase in sperm density reduced the number of sperms tracked from both trackers. With more than 50 sperms in the field of view, NN and MHT tracked 73% and 92% of the ground‐truth sperm count, respectively. Both trackers showed a quadratic increase in tracking errors with increasing sperm density. The maximum percentage of errors at 90% motility was 12% for NN and 4.7% for MHT. The MHT tracker required up to 150 s to track 300 sperms, whereas NN completed the tracking procedure in less than 0.5 s. On maintaining a density of up to 100 sperms in the field of view, it was possible to obtain high accuracy, low number of tracking errors and an acceptable analysis duration with both tracking methods.