Results 11 to 20 of about 14,186,648 (294)

Dual-Stream STGCN with Motion-Aware Grouping for Rehabilitation Action Quality Assessment [PDF]

Sensors
Action quality assessment automates the evaluation of human movement proficiency, which is vital for applications like sports training and rehabilitation, where objective feedback enhances patient outcomes.
Zhejun Kuang, Zhaotin Yin, Yuheng Yang, Jian Zhao, Lei Sun   +4 more
doaj   +2 more sources

RESC: A Rubric-Guided Error–Score Consistency Framework for Action Quality Assessment in Vocational Fitter Training [PDF]

Sensors
Action quality assessment in vocational fitter training is constrained by limited expert-annotated data and insufficiently interpretable predictions. To achieve accurate scoring and rubric-aligned, auditable explanations with limited data, this study ...
Wenfeng Mu, Shigang Wang, Jiajia Huang
doaj   +2 more sources

Skeleton-Based Action Quality Assessment with Anomaly-Aware DTW Optimization for Intelligent Sports Education [PDF]

Sensors
In intelligent sports education, current action quality assessment (AQA) methods face significant limitations: regression-based methods are heavily dependent on high-quality annotated data, while unsupervised methods lack sufficient accuracy and degrade ...
Wen Fu, Wenze Fang, Jiahao Huang, Kexin Zhu, Renguang Chen, Chen Feng   +5 more
doaj   +2 more sources

Enhancing Long-Term Action Quality Assessment: A Dual-Modality Dataset and Causal Cross-Modal Framework for Trampoline Gymnastics [PDF]

Sensors
Action quality assessment (AQA) plays a pivotal role in intelligent sports analysis, aiding athlete training and refereeing decisions. However, existing datasets and methods are limited to short-term actions, lacking comprehensive spatiotemporal modeling
Fengyan Lin, Jiahao Huang, Zhide Chen, Kexin Zhu, Chen Feng   +4 more
doaj   +2 more sources

C-TransDance: A Style-Conditioned Gated CNN–Transformer for Real-Time Multi-Style Dance Quality Assessment Using Vision-Based Pose Sensing [PDF]

Sensors
Vision-based human motion assessment requires a model to capture both temporal execution patterns and context-dependent quality criteria. This problem is particularly challenging in multi-style dance, where similar kinematic patterns may receive ...
Shan Zhang, Yantong Liu, Seong-Yoon Shin, Hyun-Ae Lee   +3 more
doaj   +2 more sources

LLM-FMS: A fine-grained dataset for functional movement screen action quality assessment. [PDF]

PLoS ONE
The Functional Movement Screen (FMS) is a critical tool for assessing an individual's basic motor abilities, aiming to prevent sports injuries. However, current automated FMS evaluation is based on deep learning methods, and the evaluation of actions is ...
Qingjun Xing, Xuyang Xing, Ping Guo, Zhenhui Tang, Yanfei Shen   +4 more
doaj   +3 more sources

Semantic-aware self-supervised learning using progressive sub-action regression for action quality assessment [PDF]

Scientific Reports
Action Quality Assessment (AQA) is a growing field in computer vision that focuses on objectively evaluating human actions from videos, with applications across various domains.
Marjan Mazruei, Ehsan Fazl-Ersi, Abedin Vahedian, Ahad Harati   +3 more
doaj   +2 more sources

Athlete action quality assessment based on transfer neural network quality score decoupling in complex sports scenarios [PDF]

Scientific Reports
Action quality assessment (AQA) is an important and challenging task in computer vision, which has received wide attention in many fields, especially in sports video analysis.
Lei Gao, Yuhong Ma, Sijuan Bi, Shuangjun Li   +3 more
doaj   +2 more sources

Integrating visual transformers with biomechanical constraints for action quality assessment in competitive sports [PDF]

Scientific Reports
Assessing how well an athlete performs a specific movement—rather than simply identifying what movement was performed—remains one of the harder open problems at the intersection of computer vision and sports science.
Li Shicen
doaj   +2 more sources

On Action Quality Assessment [PDF]

, 2019
In this dissertation, we tackle the task of quantifying the quality of actions, i.e., how well an action was performed using computer vision. Existing methods used human body pose-based features to express the quality contained in an action sample.
Parmar, Paritosh
openaire   +2 more sources