A three-dimensional virtual mouse generates synthetic training data for behavioral analysis

Published in Nature Methods, 2021

Recommended citation: Luis A. Bolaños, Dongsheng Xiao, Nancy L. Ford, Jeff M. LeDue, Pankaj K. Gupta, Carlos Doebeli, Hao Hu, Helge Rhodin & Timothy H. Murphy https://www.nature.com/articles/s41592-021-01103-9

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We developed a three-dimensional (3D) synthetic animated mouse based on computed tomography scans that is actuated using animation and semirandom, joint-constrained movements to generate synthetic behavioral data with ground-truth label locations. Image-domain translation produced realistic synthetic videos used to train two-dimensional (2D) and 3D pose estimation models with accuracy similar to typical manual training datasets. The outputs from the 3D model-based pose estimation yielded better definition of behavioral clusters than 2D videos and may facilitate automated ethological classification.

Recommended citation: Luis A. Bolaños, Dongsheng Xiao, Nancy L. Ford, Jeff M. LeDue, Pankaj K. Gupta, Carlos Doebeli, Hao Hu, Helge Rhodin & Timothy H. Murphy