Posture-based and action-based graphs for boxing skill visualization

Shen, Yijun; Wang, He; Ho, Edmond S. L.; Yang, Longzhi; Shum, Hubert P. H.

doi:10.1016/j.cag.2017.09.007

Cited by 13 publications

(13 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [13], the posture-based graph method was applied to analyze the movements, while the shadow boxing motions of the boxer were captured using an optical motion capture system. Visualization of movements was one of the main objectives of the study.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

Khasanshin

2021

Applied Sciences

View full text Add to dashboard Cite

This work aimed to study the automation of measuring the speed of punches of boxers during shadow boxing using inertial measurement units (IMUs) based on an artificial neural network (ANN). In boxing, for the effective development of an athlete, constant control of the punch speed is required. However, even when using modern means of measuring kinematic parameters, it is necessary to record the circumstances under which the punch was performed: The type of punch (jab, cross, hook, or uppercut) and the type of activity (shadow boxing, single punch, or series of punches). Therefore, to eliminate errors and accelerate the process, that is, automate measurements, the use of an ANN in the form of a multilayer perceptron (MLP) is proposed. During the experiments, IMUs were installed on the boxers’ wrists. The input parameters of the ANN were the absolute acceleration and angular velocity. The experiment was conducted for three groups of boxers with different levels of training. The developed model showed a high level of punch recognition for all groups, and it can be concluded that the use of the ANN significantly accelerates the collection of data on the kinetic characteristics of boxers’ punches and allows this process to be automated.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Here, a very interesting approach to movement recognition is applied-tracking poses when moving. As the authors write in [13], "the posture-based graph focuses on evaluating the common postures that are used to start and end actions. In such a graph, the nodes represent similar postures and the edges represent similar actions".…”

Section: Related Workmentioning

confidence: 99%

Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

Khasanshin

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…In this section, we will first review existing examples of AR in various industries. While Virtual Reality (VR) and interactive computer graphics have been used for teaching and learning, such as partner dancing [3], visualizing wrestling [4], [5] and boxing [6], [7] skills, in the last two decades, more attention has been paid on vision-based frameworks which make use of cameras and sensors. By capturing the information from the surrounding using cameras and sensors, useful feedback can be provided to the user, such as posture monitoring [8] and interacting with virtual objects using body movement [9], [10].…”

Section: Related Workmentioning

confidence: 99%

NETIVAR: NETwork Information Visualization based on Augmented Reality

Flinton

Anderson

Shum

et al. 2018

2018 12th International Conference on Software, Knowledge, Information Management &Amp; Applications (SKIMA)

View full text Add to dashboard Cite

Connecting network cables to network switches is a time-consuming and inefficient task, and requires extensive documentation and preparation beforehand to ensure no service faults are encountered by the users. In this paper, a new AR smartphone application that overlays network switch information over the user's vision is designed and developed for real working environment to increase user's efficiency in working with a network switch. Specifically, the prototype of the AR App is developed on the Android platform using both the Unity game engine and Vuforia AR library and connecting to the network switch to retrieve network information through telnet. By using the camera on the smartphone for capturing the visual information from the working environment, i.e. the network switch in this App, the network switch information such as speed, types, etc. will be overlaid on each port on the smartphone screen. A user study was conducted to evaluate the effectiveness of the AR App to assist users in performing network tasks. In particular, participants were tasked with connecting switchports to a patch panel to match up corresponding configurations. After three tests, it was found that the times for completion and mistakes made were reduced in the final test when compared to the first. This highlights the positive effects of the application in improving the user's efficiency.

show abstract

“…Early methods formulate in-between motions as motion planning problem [Wang et al 2015[Wang et al , 2013Ye and Liu 2010], which requires solving complex optimizations and are prohibitively slow for real-time applications. Data-driven methods have also been developed [Kovar et al 2008;Min and Chai 2012;Shen et al 2017]. However, to handle arbitrary in-between motions and target frames, the size of needed data in memory grows exponentially [Harvey et al 2020].…”

Section: Introductionmentioning

confidence: 99%

Real-time Controllable Motion Transition for Characters

Tang,

Wang,

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Fig. 1. In-between motion sequences (blue) between target frames (orange) generated by our method. Given a target frame and a desired transition duration, the controlled character can dynamically adjust strategies, e.g., different step sizes, velocities, or motion types, to reach the target without visual artifacts.Real-time in-between motion generation is universally required in games and highly desirable in existing animation pipelines. Its core challenge lies in the need to satisfy three critical conditions simultaneously: quality, controllability and speed, which renders any methods that need offline computation (or post-processing) or cannot incorporate (often unpredictable) user control undesirable. To this end, we propose a new real-time transition method to address the aforementioned challenges. Our approach consists of two key

show abstract

Posture-based and action-based graphs for boxing skill visualization

Cited by 13 publications

References 29 publications

Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

NETIVAR: NETwork Information Visualization based on Augmented Reality

Real-time Controllable Motion Transition for Characters

Contact Info

Product

Resources

About