Temporal Hockey Action Recognition via Pose and Optical Flows
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- Type
- preprint
- Published
- 2018-12-22
- Cited by
- 41
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W2905655267
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:56895544
Keywords
Optical flow, Computer science, Pose, Artificial intelligence, Ice hockey
References
- Tracking and Recognizing Actions at a Distance
- Self-Learning for Player Localization in Sports Video
- Learning Spatiotemporal Features with 3D Convolutional Networks
- Real-time visual play-break detection in sport events using a context descriptor
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- P-CNN: Pose-Based CNN Features for Action Recognition
- Joint action recognition and pose estimation from video
- Beyond short snippets: Deep networks for video classification
- Long-term recurrent convolutional networks for visual recognition and description
- Better Exploiting Motion for Better Action Recognition
- Large-Scale Video Classification with Convolutional Neural Networks
- Towards Understanding Action Recognition
- Video analysis of hockey play in selected game situations
- Condensation-based multi-person detection and tracking with HOG and LBP
- Latent Hierarchical Model of Temporal Structure for Complex Activity Classification
- Dense Trajectories and Motion Boundary Descriptors for Action Recognition
- Coupled Action Recognition and Pose Estimation from Multiple Views
- 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
- Temporal Localization of Actions with Actoms
- Tracking and recognizing actions of multiple hockey players using the boosted particle filter
Cited by
- Two-Stream Action Recognition in Ice Hockey using Player Pose Sequences and Optical Flows
- Prediction of Future Shot Direction using Pose and Position of Tennis Player
- A Context-Aware Loss Function for Action Spotting in Soccer Videos
- An Automated System for Generating Tactical Performance Statistics for Individual Soccer Players From Videos
- Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions
- Group Activity Detection from Trajectory and Video Data in Soccer
- TTNet: Real-time temporal and spatial video analysis of table tennis
- Improved Soccer Action Spotting using both Audio and Video Streams
- A System for Acquisition and Modelling of Ice-Hockey Stick Shape Deformation from Player Shot Videos
- DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera
- Multi-Scale Enhanced Active Learning for Skeleton-Based Action Recognition
- A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical Exercise
- Deep Learning-Based Action Detection in Untrimmed Videos: A Survey
- Sports Intelligent Assistance System Based on Deep Learning
- Self-supervised 3D human pose estimation from video
- A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions
- An overview of Human Action Recognition in sports based on Computer Vision
- Learning cricket strokes from spatial and motion visual word sequences
- Interaction Classification with Key Actor Detection in Multi-Person Sports Videos
- Ice hockey player identification via transformers and weakly supervised learning
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