Search Results for author: Rikuhei Umemoto

Found 3 papers, 2 papers with code

TeamTrack: A Dataset for Multi-Sport Multi-Object Tracking in Full-pitch Videos

no code implementations22 Apr 2024 Atom Scott, Ikuma Uchida, Ning Ding, Rikuhei Umemoto, Rory Bunker, Ren Kobayashi, Takeshi Koyama, Masaki Onishi, Yoshinari Kameda, Keisuke Fujii

Multi-object tracking (MOT) is a critical and challenging task in computer vision, particularly in situations involving objects with similar appearances but diverse movements, as seen in team sports.

Evaluating Soccer Match Prediction Models: A Deep Learning Approach and Feature Optimization for Gradient-Boosted Trees

1 code implementation26 Sep 2023 Calvin Yeung, Rory Bunker, Rikuhei Umemoto, Keisuke Fujii

The original training set of matches and features, which was provided for the competition, was augmented with additional matches that were played between 4 April and 13 April 2023, representing the period after which the training set ended, but prior to the first matches that were to be predicted (upon which the performance was evaluated).

Location analysis of players in UEFA EURO 2020 and 2022 using generalized valuation of defense by estimating probabilities

1 code implementation30 Nov 2022 Rikuhei Umemoto, Kazushi Tsutsui, Keisuke Fujii

Using the open-source location data of all players in broadcast video frames in football games of men's Euro 2020 and women's Euro 2022, we investigated the effect of the number of players on the prediction and validated our approach by analyzing the games.

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