paper-with-me

홈 › Papers

PLayerTV: Advanced Player Tracking and Identification for Automatic Soccer Highlight Clips

2024-07-22 · Håkon Maric Solberg, Mehdi Houshmand Sarkhoosh, Sushant Gautam, Saeed Shafiee Sabet, Pål Halvorsen, Cise Midoglu

In the rapidly evolving field of sports analytics, the automation of targeted video processing is a pivotal advancement. We propose PlayerTV, an innovative framework which harnesses state-of-the-art AI technologies for automatic player tracking and identification in soccer videos. By integrating object detection and tracking, Optical Character Recognition (OCR), and color analysis, PlayerTV facilitates the generation of player-specific highlight clips from extensive game footage, significantly reducing the manual labor traditionally associated with such tasks. Preliminary results from the evaluation of our core pipeline, tested on a dataset from the Norwegian Eliteserien league, indicate that PlayerTV can accurately and efficiently identify teams and players, and our interactive Graphical User Interface (GUI) serves as a user-friendly application wrapping this functionality for streamlined use.

📄 PDF Abstract BibTeX arXiv:2407.16076

Code (0)

등록된 구현이 없습니다.

Tasks

object-detectionObject DetectionOptical Character RecognitionOptical Character Recognition (OCR)Sports Analytics

Similar Papers 제목 키워드 기반

Player Tracking and Identification in Ice Hockey

2021-10-06 · Kanav Vats, Pascale Walters, Mehrnaz Fani, David A. Clausi 외

Tracking and identifying players is a fundamental step in computer vision-based ice hockey analytics. The data generated by tracking is used in many other downstream tasks, such as game event detection and game strategy …

Event DetectionMulti-Object TrackingObject Tracking

Efficient tracking of team sport players with few game-specific annotations

2022-04-08 · Adrien Maglo, Astrid Orcesi, Quoc-Cuong Pham

One of the requirements for team sports analysis is to track and recognize players. Many tracking and reidentification methods have been proposed in the context of video surveillance. They show very convincing results wh…

Incremental Learning

Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking

2024-01-18 · Amir M. Mansourian, Vladimir Somers, Christophe De Vleeschouwer, Shohreh Kasaei

Effective tracking and re-identification of players is essential for analyzing soccer videos. But, it is a challenging task due to the non-linear motion of players, the similarity in appearance of players from the same t…

Multi-Task LearningVisual Tracking

Evaluating deep tracking models for player tracking in broadcast ice hockey video

2022-05-22 · Kanav Vats, Mehrnaz Fani, David A. Clausi, John S. Zelek

Tracking and identifying players is an important problem in computer vision based ice hockey analytics. Player tracking is a challenging problem since the motion of players in hockey is fast-paced and non-linear. There i…

Automated player identification and indexing using two-stage deep learning network

2022-04-26 · Hongshan Liu, Colin Aderon, Noah Wagon, Abdul Latif Bamba 외

American football games attract significant worldwide attention every year. Identifying players from videos in each play is also essential for the indexing of player participation. Processing football game video presents…

Jersey Number Recognitionobject-detectionObject Detection