Problem
Research questions and friction points this paper is trying to address.
WiFi Channel State Information
Optical Flow Estimation
Privacy Concerns
WiFlow: Estimating Optical Flow using WiFi Channel State Information
🤖 AI Summary
本文提出使用WiFi信道状态信息替代摄像头来估计光流，以解决隐私和光照条件限制的问题，并设计了WiFlow模型及相应数据集。
📝 Abstract
Knowing where and how fast objects are moving within a scene is important across various domains. Usually, cameras are used to capture the data necessary for this task, but adding cameras often raises privacy concerns, and the quality of captured frames is heavily influenced by lighting conditions. In this work, we explore using WiFi channel state information (CSI) instead of camera frames for optical flow estimation. We propose WiFlow, a CSI based flow estimator, a preprocessor evaluation for CSI, and three model architectures that offer different trade-offs between accuracy and complexity. Further, we create the first dataset for training and evaluating CSI-based optical flow estimators, and our experiments provide insights into key design elements for this task. Code and data are available at https://visinf.github.io/wiflow.
Innovation
Methods, ideas, or system contributions that make the work stand out.
WiFi Channel State Information
Optical Flow Estimation
Privacy
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