A Two-Stage Learning Approach for Goalie, Net and Stick Pose Estimation in Ice Hockey
| dc.contributor.author | Shahi, Fatemeh | |
| dc.date.accessioned | 2023-09-26T14:20:35Z | |
| dc.date.available | 2023-09-26T14:20:35Z | |
| dc.date.issued | 2023-09-26 | |
| dc.date.submitted | 2023-09-13 | |
| dc.description.abstract | Accurate pose estimation of ice hockey goaltenders presents a unique challenge due to the dynamic nature of the sport and the intricate interactions among the goalie, equipment, and net. This study introduces a comprehensive investigation into goalie pose estimation using both One-Stage and Two-Stage Learning GoalieNet architectures. The One-Stage Learning GoalieNet predicts all keypoints simultaneously, while the Two-Stage Learning GoalieNet employs a Keypoint Predictor Network (KPN) to predict 26 out of 29 keypoints and a Keyheatmap Fusion Network (KFN) to predict 3 stick-related keypoints. Evaluation on a NHL dataset underscores the effectiveness of both approaches in accurately predicting keypoints. Results on the test data reveal a median percentage of detected keypoints of 71% for the Two-Stage approach and 70% for the One-Stage approach, along with normalized localization errors on detected keypoints of 0.0187 for the Two-Stage and 0.0194 for the One-Stage approach. This work introduces the first-ever goalie pose estimation technique designed specifically for ice hockey, accompanied by a thorough analysis of the obtained results. | en |
| dc.identifier.uri | http://hdl.handle.net/10012/19949 | |
| dc.language.iso | en | en |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.title | A Two-Stage Learning Approach for Goalie, Net and Stick Pose Estimation in Ice Hockey | en |
| dc.type | Master Thesis | en |
| uws-etd.degree | Master of Applied Science | en |
| uws-etd.degree.department | Systems Design Engineering | en |
| uws-etd.degree.discipline | System Design Engineering | en |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws-etd.embargo.terms | 0 | en |
| uws.comment.hidden | The related dataset and code repository is private due as it is requested by the company provided the data. Also, my supervisors are David A. Clausi and Alexander Wong. I tried numerous times to use add button in supervisors part, but it seems it just maintain the name entered in the field, not the one added using add. It seems the same problem occur with the keywords part. I emailed to uwlibrary support, but as my deadline is approaching, I proceed with the submit. | en |
| uws.contributor.advisor | Wong, Alexander | |
| uws.contributor.affiliation1 | Faculty of Engineering | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.published.city | Waterloo | en |
| uws.published.country | Canada | en |
| uws.published.province | Ontario | en |
| uws.scholarLevel | Graduate | en |
| uws.typeOfResource | Text | en |