[HTML][HTML] An overview of Human Action Recognition in sports based on Computer Vision
K Host, M Ivašić-Kos - Heliyon, 2022 - cell.com
Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …
[HTML][HTML] A comprehensive review of computer vision in sports: Open issues, future trends and research directions
Recent developments in video analysis of sports and computer vision techniques have
achieved significant improvements to enable a variety of critical operations. To provide …
achieved significant improvements to enable a variety of critical operations. To provide …
An end-to-end spatio-temporal attention model for human action recognition from skeleton data
Human action recognition is an important task in computer vision. Extracting discriminative
spatial and temporal features to model the spatial and temporal evolutions of different …
spatial and temporal features to model the spatial and temporal evolutions of different …
Spatio-temporal autoencoder for video anomaly detection
Anomalous events detection in real-world video scenes is a challenging problem due to the
complexity of" anomaly" as well as the cluttered backgrounds, objects and motions in the …
complexity of" anomaly" as well as the cluttered backgrounds, objects and motions in the …
Learning actor relation graphs for group activity recognition
Modeling relation between actors is important for recognizing group activity in a multi-person
scene. This paper aims at learning discriminative relation between actors efficiently using …
scene. This paper aims at learning discriminative relation between actors efficiently using …
Spatiotemporal co-attention recurrent neural networks for human-skeleton motion prediction
Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …
A hierarchical deep temporal model for group activity recognition
In group activity recognition, the temporal dynamics of the whole activity can be inferred
based on the dynamics of the individual people representing the activity. We build a deep …
based on the dynamics of the individual people representing the activity. We build a deep …
Machine and deep learning for sport-specific movement recognition: A systematic review of model development and performance
Objective assessment of an athlete's performance is of importance in elite sports to facilitate
detailed analysis. The implementation of automated detection and recognition of sport …
detailed analysis. The implementation of automated detection and recognition of sport …
Coherence constrained graph LSTM for group activity recognition
This work aims to address the group activity recognition problem by exploring human motion
characteristics. Traditional methods hold that the motions of all persons contribute equally to …
characteristics. Traditional methods hold that the motions of all persons contribute equally to …
HiGCIN: Hierarchical graph-based cross inference network for group activity recognition
Group activity recognition (GAR) is a challenging task aimed at recognizing the behavior of a
group of people. It is a complex inference process in which visual cues collected from …
group of people. It is a complex inference process in which visual cues collected from …