A novel dynamic segmentation approach based on spearman correlation for human activity recognition

Key Points

• Enhanced activity recognition accuracy is achieved using a novel dynamic segmentation approach based on spearman correlation.
• The model utilizes advanced pattern analysis to differentiate human activities effectively across multiple contexts.
• Assessment employs feature extraction techniques to optimize the recognition rate for various activities.
• This approach may enable real-time tracking in diverse applications, though real-world testing is still needed.