Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition

Understand

Landmark-based human action recognition in videos is a challenging task in computer vision.

• One key step is to design a generic approach that generates discriminative features for the spatial structure and temporal dynamics.
• To this end, we regard the evolving landmark data as a high-dimensional path and apply non-linear path signature techniques to provide an expressive, robust, non-linear, and interpretable representation for the sequential events.
• We do not extract signature features from the raw path, rather we propose path disintegrations and path transformations as preprocessing steps.