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Wi-Fi Passive Person Re-Identification based on Channel State Information

2019-11-12 14:42:02
Danilo Avola, Marco Cascio, Luigi Cinque, Daniele Pannone

Abstract

With the increasing need for wireless data transfer, Wi-Fi networks have rapidly grown in recent years providing high throughput and easy deployment. Nowadays, Access Points (APs) can be found easily wherever we go, therefore Wi-Fi sensing applications have caught a great deal of interest from the research community. Since human presence and movement influence the Wi-Fi signals transmitted by APs, it is possible to exploit those signals for person Re-Identification (Re-ID) task. Traditional techniques for Wi-Fi sensing applications are usually based on the Received Signal Strength Indicator (RSSI) measurement. However, recently, due to the RSSI instability, the researchers in this field propose Channel State Information (CSI) measurement based methods. In this paper we explain how changes in Signal Noise Ratio (SNR), obtained from CSI measurements, combined with Neural Networks can be used for person Re-ID achieving remarkable preliminary results. Due to the lack of available public data in the current state-of-the-art to test such type of task, we acquired a dataset that properly fits the aforementioned task.

Abstract (translated)

URL

https://arxiv.org/abs/1911.04900

PDF

https://arxiv.org/pdf/1911.04900.pdf


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3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot