3D-unified spatial-temporal graph for group activity recognition
… We aim to improve group activity recognition based on these two problems. … Meanwhile,
we also establish a confusion matrix for the results of different behavior predictions in collective …
we also establish a confusion matrix for the results of different behavior predictions in collective …
A CSI-based multi-environment human activity recognition framework
… different performed activities. To validate the performance of the proposed approach, we
collected data in two different environments. In each of the environments, several activities were …
collected data in two different environments. In each of the environments, several activities were …
Ultra-wideband radar-based activity recognition using deep learning
… algorithms to the dataset for comparative and performance analyses. SVM [50], introduced by
… function to make predictions for five classes. Our model has 847,055 trainable parameters. …
… function to make predictions for five classes. Our model has 847,055 trainable parameters. …
Pose-appearance relational modeling for video action recognition
… (PARNet) is proposed for robust action recognition based on 2D poses and video frames. …
estimator and action recognizer into an unified framework and makes prediction based on both …
estimator and action recognizer into an unified framework and makes prediction based on both …
Attend and discriminate: Beyond the state-of-the-art for human activity recognition using wearable sensors
… wrongly predicting Null class when an activity exists. … of our model to predict a continuous
sequence of activity labels that … Human activity recognition based on wearable sensor data: A …
sequence of activity labels that … Human activity recognition based on wearable sensor data: A …
Human activity recognition through deep learning: Leveraging unique and common feature fusion in wearable multi-sensor systems
K Liu, C Gao, B Li, W Liu - Applied Soft Computing, 2024 - Elsevier
… for enhanced activity prediction. Their models demonstrated superior performance by … -sensor
fusion method for human activity recognition based on deep learning. This method …
fusion method for human activity recognition based on deep learning. This method …
A survey on human group activity recognition by analysing person action from video sequences using machine learning techniques
S Kulkarni, S Jadhav, D Adhikari - Optimization in machine learning and …, 2020 - Springer
… Thus, it is essential to develop techniques for online activity recognition based on automatic
… for action recognition in video which motivates directly to predict sequential bounds of …
… for action recognition in video which motivates directly to predict sequential bounds of …
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition
… action movement localization and action recognition. A slightly more abstract problem is activity
… of abstraction we have motion or behavior understanding and prediction. OpenPose [16] …
… of abstraction we have motion or behavior understanding and prediction. OpenPose [16] …
Accurate physical activity recognition using multidimensional features and Markov model for smart health fitness
… This paper provides a unified framework that explores … , healthcare systems and human
behavior analysis. In security … due to the prediction of future players’ actions and the expected …
behavior analysis. In security … due to the prediction of future players’ actions and the expected …
Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
… [51], and EMG sensors are also used for human activity recognition. Hand movement
recognition based on EMG measurement has been widely used in computer and automatic video …
recognition based on EMG measurement has been widely used in computer and automatic video …