Parsing human skeletons in an operating room

Multiple human pose estimation is an important yet challenging problem. In an Operating Room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algorithm for localizing and recovering body poses of multiple human in an OR environment under a multi-camera setup. Our model builds on 3D Pictorial Structures (3DPS) and 2D body part localization across all camera views, using Convolutional Neural Networks (ConvNets). To evaluate our algorithm, we introduce a dataset captured in a real OR environment. Our dataset is unique, challenging and publicly available with annotated ground truths. Our proposed algorithm yields to promising pose estimation results on this dataset.


Published in:
Machine Vision and Applications, 27, 7, 1035-1046
Year:
2016
Publisher:
New York, Springer Verlag
ISSN:
0932-8092
Keywords:
Laboratories:




 Record created 2016-07-25, last modified 2018-09-13

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