TRAJECTORY STUDY OF BALLROOM DANCE USING MILLISECOND VIDEO ANALYSIS

A short video (3 s) of the natural turn movements of ballroom dance was analyzed using two-dimensional trajectory analysis to demonstrate precise verification of the movement. The movements were recorded with a high-speed camera (240 Hz), and the trajectory was plotted at 4 ms intervals. The precise trajectories of test subjects’ movements were successfully monitored by making them wear LED lights on their necks, elbows, waists, and knees. The differences between the trajectories of an experienced subject’s movement and that of a beginner were clearly indicated, even when those movements occurred over short durations. The differences were also evident from a velocity analysis of the same video data. Our low-cost method can be applied to ballroom dance education, even in a personal dance studio

Prediction of the Ball Location on the 2D Plane in Football Using Optical Tracking Data

Tracking the ball location is essential for automated game analysis in complex ball-centered team sports such as football. However, it has always been a challenge for image processing-based techniques because the players and other factors often occlude the view of the ball. This study proposes an automated machine learning-based method for predicting the ball location from players' behavior on the pitch. The model has been built by processing spatial information of players acquired from optical tracking data. Optical tracking data include samples from 300 matches of the 2017-2018 season of the Turkish Football Federation's Super League. We use neural networks to predict the ball location in 2D axes. The average coefficient of determination of the ball tracking model on the test set both for the x-axis and the y-axis is accordingly 79% and 92%, where the mean absolute error is 7.56 meters for the x-axis and 5.01 meters for the y-axi

Tracking of a Basketball Using Multiple Cameras

Projecte final de carrera fet en copl.laboració amb École Polytechnique Fédérale de LaussanneThis master thesis presents a method for tracking a basketball during a basketball match recorded with a multi-camera system. We first developed methods to detect a ball in images based on its appearance. Color was used through a color histogram of the ball, manually initialized with ball samples. Then the shape of the ball was used in two different ways: by analyzing the circularity of the ball contour and by using the Hough transform to find circles in the image. In a second step, we attempted to track the ball in three dimensions using the cameras calibration, as well as the image methods previously developed. Using a recursive tracking procedure, we define a 3-dimensional search volume around the previously known position of the ball and evaluate the presence of a ball in all candidate positions inside this volume. This is performed by projecting the candidate positions in all camera views and checking the ball presence using color and shape cues. Extrapolating the future position of the ball based on its movements in the past frames was also tested to make our method more robust to motion blur and occlusions. Evaluation of the proposed algorithm has been done on a set of synchronized multi-camera sequences. The results have shown that the algorithm can track the ball and find its 3D position during several consecutive frames

Tracking of a Basketball Using Multiple Cameras

Projecte final de carrera fet en copl.laboració amb École Polytechnique Fédérale de LaussanneThis master thesis presents a method for tracking a basketball during a basketball match recorded with a multi-camera system. We first developed methods to detect a ball in images based on its appearance. Color was used through a color histogram of the ball, manually initialized with ball samples. Then the shape of the ball was used in two different ways: by analyzing the circularity of the ball contour and by using the Hough transform to find circles in the image. In a second step, we attempted to track the ball in three dimensions using the cameras calibration, as well as the image methods previously developed. Using a recursive tracking procedure, we define a 3-dimensional search volume around the previously known position of the ball and evaluate the presence of a ball in all candidate positions inside this volume. This is performed by projecting the candidate positions in all camera views and checking the ball presence using color and shape cues. Extrapolating the future position of the ball based on its movements in the past frames was also tested to make our method more robust to motion blur and occlusions. Evaluation of the proposed algorithm has been done on a set of synchronized multi-camera sequences. The results have shown that the algorithm can track the ball and find its 3D position during several consecutive frames

Monitorização da trajetória de uma bola num jogo de ténis de mesa

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Área de Especialização de Automação. Faculdade de Engenharia. Universidade do Porto. 201

高速かつ変則的に移動する物体の軌跡推定法

筑波大学 (University of Tsukuba)201