Pose estimation is the problem of detecting poses of people in images, multiperson pose estimation is the problem of detecting poses of multiple persons in images. This thesis investigates multi-person pose estimation by applying the associative embedding method on images from soccer videos. Three models are compared, first a pre-trained model, second a fine-tuned model and third a model extended to handle image sequences. The pre-trained method performed well on soccer images and the fine-tuned model performed better then the pre-trained model. The image sequence model performed equally as the fine-tuned model but not better. This thesis concludes that the associative embedding model is a feasible option for pose estimation in soccer videos and should be further researched.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-148871 |
| Date | January 2018 |
| Creators | Skyttner, Axel |
| Publisher | Linköpings universitet, Matematisk statistik, Linköpings universitet, Tekniska fakulteten, Signality |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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