Self-Supervised WiFi-Based Activity Recognition
Traditional approaches to activity recognition involve the use of wearable sensors or cameras in order to recognise human activities. In this work, we extract fine-grained physical layer information from WiFi devices for the purpose of passive activity recognition in indoor environments. While such data is ubiquitous, few approaches are designed to utilise large amounts of unlabelled WiFi data. We propose the use of self-supervised contrastive learning to improve activity recognition performance when using multiple views of the transmitted WiFi signal captured by different synchronised receivers. We conduct experiments where the transmitters and receivers are arranged in different physical layouts so as to cover both Line-of-Sight (LoS) and non LoS (NLoS) conditions. We compare the proposed contrastive learning system with non-contrastive systems and observe a 17.7% increase in macro averaged F1 score on the task of WiFi based activity recognition, as well as significant improvements in one- and few-shot learning scenarios.
Code (0)
등록된 구현이 없습니다.
Tasks
Activity RecognitionContrastive LearningFew-Shot LearningMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Antenna Response Consistency Driven Self-supervised Learning for WIFI-based Human Activity Recognition
Self-supervised learning (SSL) for WiFi-based human activity recognition (HAR) holds great promise due to its ability to address the challenge of insufficient labeled data. However, directly transplanting SSL algorithms,…
Activity RecognitionARCAttributeContrastive Learning+2MaskFi: Unsupervised Learning of WiFi and Vision Representations for Multimodal Human Activity Recognition
Human activity recognition (HAR) has been playing an increasingly important role in various domains such as healthcare, security monitoring, and metaverse gaming. Though numerous HAR methods based on computer vision have…
Activity RecognitionHuman Activity RecognitionRepresentation LearningAutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised Learning
WiFi sensing technology has shown superiority in smart homes among various sensors for its cost-effective and privacy-preserving merits. It is empowered by Channel State Information (CSI) extracted from WiFi signals and …
Activity RecognitionDomain AdaptationGait RecognitionGesture Recognition+2Joint Activity Recognition and Indoor Localization With WiFi Fingerprints
Recent years have witnessed the rapid development in the research topic of WiFi sensing that automatically senses human with commercial WiFi devices. This work falls into two major categories, i.e., the activity recognit…
Activity RecognitionIndoor LocalizationRF-based Action RecognitionSenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing
WiFi sensing has been evolving rapidly in recent years. Empowered by propagation models and deep learning methods, many challenging applications are realized such as WiFi-based human activity recognition and gesture reco…
Activity RecognitionDeep LearningGesture RecognitionHuman Activity Recognition