April 19 2023, 11:30 am, EC4-2101A

*** 11:30 am Presenter:  Bavesh Balaji ***

Description: 2D pose estimation is crucial for hockey analytics, enabling tasks like action recognition and player assessment. However, motion blur, occlusions, and crowded scenes (multiple players) hinder accurate pose estimation for both players and their held objects (e.g., hockey sticks). Existing methods, limited to predicting keypoints within an image, struggle in these scenarios. This work addresses this gap by modeling the relationship between human joints and their extensions (like hockey sticks), enabling the estimation of out-of-image keypoints.

*** 12:00pm Presenter:  Harish Prakash ***

Tracking players in sports is the fundamental first step toward several strategic, analytical, and tactical insights. But ice hockey differs from most popular sports due to its fast-paced, chaotic player dynamics that are highly intense and unpredictable. It presents several inherent challenges to monocular tracking, including motion blurs, heavy player occlusions, and significant camera motion. In this seminar, I will discuss my work on overcoming these challenges to track players across a given broadcast sequence with high fidelity. Specifically, my discussion will revolve around building a complete pipeline for localization, detection, and association of players, and the challenges faced along the way. Additionally, I will also share several ‘key’ insights obtained by curating a dataset for the same, the bias in current evaluation metrics, and potential future works along this direction.