Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners

Waghmare, Govind; Borkar, Sneha; Saley, Vishal; Chinchore, Hemant; Wabale, Shivraj

doi:10.1109/cmi.2016.7413746

Cited by 10 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…M. Gnanasekera and C. Kulasekere [2] proposed a method based on Kalman Filter to filter out the noise components of the Kalman's Estimation method, which is used to the object's position during occlusions. G. Waghmare, et al [3] developed a system for shuttlecock detection and prediction of trajectory in real time environment using two 2-D laser scanners. The results obtained by two scanners are used to predict the end point of shuttlecock trajectory.…”

Section: Related Workmentioning

confidence: 99%

Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences

Nelikanti¹,

Karuna²,

Reddy³

2019

IJITEE

View full text Add to dashboard Cite

This paper proposed a novel method for the detection and tracking of hand-thrown object in a video sequence in real time sports events. This paper mainly aimed to detect regions of the object in a set of outdoor and indoor videos in different occlusion conditions, and used Kalman filter to detect object on different trajectories over a fixed time window. This approach proved that the thrown object is successfully detected in various cases under occlusion and non-occlusion conditions with different backgrounds. To evaluate the accuracy, two different types of performance evaluations metrics are used based on object detection and tracking. The results shows that significant performance, the average accuracy of the object detecting is 97.89% and tracking is 98.35%

show abstract

Section: Related Workmentioning

confidence: 99%

Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences

Nelikanti¹,

Karuna²,

Reddy³

2019

IJITEE

View full text Add to dashboard Cite

show abstract

“…Most research focused on predicting future movements in net sports has centered around predicting the landing point of the ball or shuttlecock [3][4][5][6][7][8]. However, in badminton, the shuttlecock must be hit without bouncing and from a higher, faster forward position, making the prediction of the landing point insufficient for gaining an advantage in the game.…”

Section: Introductionmentioning

confidence: 99%

Future Prediction of Shuttlecock Trajectory in Badminton Using Player’s Information

et al. 2023

View full text Add to dashboard Cite

Video analysis has become an essential aspect of net sports, such as badminton. Accurately predicting the future trajectory of balls and shuttlecocks can significantly benefit players by enhancing their performance and enabling them to devise effective game strategies. This paper aims to analyze data to provide players with an advantage in the fast-paced rallies of badminton matches. The paper delves into the innovative task of predicting future shuttlecock trajectories in badminton match videos and presents a method that takes into account both the shuttlecock position and the positions and postures of the players. In the experiments, players were extracted from the match video, their postures were analyzed, and a time-series model was trained. The results indicate that the proposed method improved accuracy by 13% compared to methods that solely used shuttlecock position information as input, and by 8.4% compared to methods that employed both shuttlecock and player position information as input.

show abstract

“…The classic Kalman filter was also used in shuttlecock trajectory prediction in [7]. The study on the shuttlecock's aerodynamics [11] indicates its trajectory is not parabolic [12]. In addition, the classic Kalman filter is a dynamic estimation of the target using the minimum mean square error in the linear Gaussian case, which is suitable for linear systems.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…All vision detection systems require more computational resources to process the image. To reduce the computational hardware requirement, a method is proposed using a two-dimensional laser scanner to locate the shuttlecock [12]. It makes the whole robot system smaller than the systems mentioned earlier, and it has the capability to detect shuttlecocks flying at high speed.…”

Section: Introduction and Related Workmentioning

confidence: 99%

A novel method of shuttlecock trajectory tracking and prediction for a badminton robot

Zhi

Luo

et al. 2022

Robotica

View full text Add to dashboard Cite

This paper proposes an aerodynamic analysis of the shuttlecock and a novel method for predicting shuttlecock trajectory. First, we have established a shuttlecock track data set by an infrared-based binocular vision system. Then the unscented Kalman filter algorithm is designed to further filter the noise and visual recognition algorithm errors. Third, the radial basis function (RBF)-based track prediction model is designed. This method offers a concept to obtain the neural network model of different kinds of flying or moving objects. The experimental results show that the proposed method can predict the shuttlecock trajectory in real time at high accuracy and can be used for implementing the algorithm of return strategies in the near future.

show abstract

Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners

Cited by 10 publications

References 11 publications

Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences

Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences

Future Prediction of Shuttlecock Trajectory in Badminton Using Player’s Information

A novel method of shuttlecock trajectory tracking and prediction for a badminton robot

Contact Info

Product

Resources

About