Interactions involving the movement of various organisms are the central to the development of society. It is difficult for non-experts to distinguish between specific movement patterns, however, understanding such movement is important for obtaining the knowledge on the typology of collective biological behavior. It is still challenging, for example, even for a small team sport with few players. There are a variety of teamworks for accomplishing their goals. Screen-play in a basketball game is one of such teamworks, and is a good research topic because it is limited and simple, and involves only two attackers and a defensive player. Your task in this challenge is to identify if the attackers are using the screen-play in their offence from trajectories of the three players and the ball.
Two national teams play basketball games. 2D coordinates of 10 players and the ball for 94 minutes are obtained by a camera-based tracking system called SportVU in 25 fps. In this challenge, 2D coordinates of the related three players (see below) and the ball can be used.
"Screen-play" in basketball is a blocking movement. Suppose there is an offensive player (called a "user") who is going to receive a pass and shoot. A defender tries to prevent the user from shooting, however another offensive player (called a "screener") stands on the course of the defender and blocks the defender's movement. This screener's movement is called a screen-play. Please also see videos below. [link to Wikipedia]
The first video is a screen-play, and the second is a non-screen play.
These videos are not included in the dataset but this challenge is based on these trajectories (i.e., 2D coordinates).
Grant-in-Aid for Scientific Research on Innovative Areas from 2016 to 2021
Navigation is a fundamental behavior of animals including human. In navigation, the following three functions are required: the acquisition of dynamically-changing information from external and internal environment, the choice of route and destination based on the information, and the behavioral regulation to reach the destination. We aim for systems science of bio-navigation to understand the "algorithms" for the navigation of animals. To this end, we bring together experts from control engineering, data science, animal ecology, and neuroscience, and jointly work on how to measure, analyze, understand, and verify bio-navigation.
By hosting a series of competitions "Animal Behavior Challenge (ABC2018)" "Human Behavior Challenge (HBC2018)" "Mouse Behavior Challenge (MBC2020)" "Basketball Behavior Challenge: (BBC2020)", we hope to boost our understanding the algorithms for animal navigation.
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This challenge is governed by the general ChaLearn contest rules.
You may submit 5 submissions every day and 50 in total in the test-dev phase.
Submitted results are evaluated by the accuracy, widely used for binary classification problems.
It is 0 if all predictions are wrong, while 1 if perfect.
There are 382 test trajectory, and classification results should be a 382-line text file, which contains 0 (not including screen-play) or 1 (including screen-play) for each of test trajectory.
Each line has the label of the corresponding test trajectory; that is, line 0 is the label of the test trajectory 0000.csv. There is no header line.
Predicted label is binary (character):
not including screen-play: 0
including screen-play: 1
Here is an example:
================= 1 1 1 0 1 0 0 ... =================
The file name should be "test_prediction.csv", which should be zipped as a single zip file.
The zip file can have any name, but should contain a single file named "test_prediction.csv" without any folders.
You can create and check your submission zip file by using zip and unzip as follows:
$ zip yoursubmission.zip test_prediction.csv updating: test_prediction.csv (deflated 79%) $ unzip -l yoursubmission.zip Archive: yoursubmission.zip Length Date Time Name --------- ---------- ----- ---- 357417 03-22-2019 10:17 test_prediction.csv --------- ------- 357417 1 file
Classifying multi-agent trajectories in basketball into screen-play or non-screen play
A single CSV file (0000.csv, 0001.csv, ...) contains a trajectory. The first line is a header, and following lines represent the information of the location of the related players and the ball.
Float values are of the format %.02f, and fields are separated by a single comma.
Here is an example:
frame scr_x scr_y usr_x usr_y uDF_x uDF_y bal_x bal_y 0 2.89 4.74 5.49 1.5 2.78 5.22 6.98 12.7 1 2.88 4.7 5.52 1.51 2.8 5.2 7.08 12.52 2 2.87 4.67 5.54 1.53 2.82 5.19 7.13 12.35 3 2.86 4.65 5.56 1.54 2.84 5.17 7.08 12.37 ...
Trajectories are obtained by SportVU system in 25 fps. See videos at the top page. In the video, bottom-left corner is the origin (0, 0), and the positive direction of the x axis is rightward, and the positive direction of the y axis is the upward. Coordinate ranges are from 0 to 14 [m] for x and 0 to 15 [m] for y.
Training trajectories of files from 0.csv to 399.csv include screen-play.
Training trajectories of files from 400.csv to 1527.csv include non screen-play.
The training and test trajectories are different in length (from 23 to 242 frames).
Both the training and test trajectories are pre-processed in the same way.
UPDATE 2020/Sep/1: Due to the pandemic of COVID-19, the following symposium has been cancelled. We are very sorry but the travel grant will not be given to winners, and we will PDF certificates to winners as a prize.
UPDATE: Due to the pandemic of COVID-19, the following symposium MAY be cancelled in future. In such case, unfortunately the travel grant will not be given to winners and we will PDF certificates to winners as a prize.
The winner will receive the following travel grant in addition to the winner certificate.
The first winner will receive
Note that
This challenge is governed by the general ChaLearn contest rules.
Start: Dec. 1, 2019, 3 p.m.
Description: Submit your results on the test set. Show one of results to the leaderboard, which is used for the test-challenge phase.
Start: Aug. 31, 2020, 2:59 p.m.
Description: Final phase. you don't submit any results. Instead, the result shown in the leaderboard of the test-dev phase is used for the final evaluataion.
Sept. 1, 2020, 2:59 p.m.
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