Work

Radar Based Human Activity Recognition: from Classification to Detection

Year: 2024

Type: conference-paper

Abstract: FMCW radar is emerging as a key technology for contactless Human Activity Recognition (HAR) in medical settings. While effective in controlled environments, FMCW radar-based HAR faces challenges in realistic scenarios, particularly with continuous data streams. Tradi- tional methods often rely on segmentation, which can be cumbersome, or fail to handle transitions between activities, leading to errors. This study introduces a novel approach that enhances activity detection by refining classifier outputs with simple probabilistic reasoning that takes into account activity transition probabilities. The proposed method im- proves the HAR detection F1 score with 6% compared to the baseline and even slightly improves the classification accuracy which does not take into historical information about previous activities.

Source: Lirias

Authors: El Hail, Reda, Mehrjouseresht, Pouya, Babarinde, Oluwatosin John, Schreurs, Dominique, Karsmakers, Peter

Institutions: KU Leuven, Flanders Make (Belgium)

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Electronic Components and Systems for European Leadership, Horizon 2020 Framework Programme

Awards: G3379343234, G4650711970