Search Results for author: Marco Gruteser

Found 14 papers, 5 papers with code

ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements

1 code implementation MobiCom ISACom 2023 Bryan Bo Cao, Abrar Alali, Hansi Liu, Nicholas Meegan, Marco Gruteser, Kristin Dana, Ashwin Ashok, Shubham Jain

Tracking subjects in videos is one of the most widely used functions in camera-based IoT applications such as security surveillance, smart city traffic safety enhancement, vehicle to pedestrian communication and so on.

ViFi-Loc: Multi-modal Pedestrian Localization using GAN with Camera-Phone Correspondences

no code implementations22 Nov 2022 Hansi Liu, Kristin Dana, Marco Gruteser, HongSheng Lu

During inference, it generates refined position estimations based only on pedestrians' phone data that consists of GPS, IMU and FTM.

Self-Learning Sensor Fusion

ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning

no code implementations11 Oct 2022 Nicholas Meegan, Hansi Liu, Bryan Cao, Abrar Alali, Kristin Dana, Marco Gruteser, Shubham Jain, Ashwin Ashok

We introduce ViFiCon, a self-supervised contrastive learning scheme which uses synchronized information across vision and wireless modalities to perform cross-modal association.

Contrastive Learning Region Proposal

Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors

1 code implementation ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) 2022 Hansi Liu, Abrar Alali, Mohamed Ibrahim, Bryan Bo Cao, Nicholas Meegan, Hongyu Li, Marco Gruteser, Shubham Jain, Kristin Dana, Ashwin Ashok, Bin Cheng, HongSheng Lu

In this paper, we present Vi-Fi, a multi-modal system that leverages a user’s smartphone WiFi Fine Timing Measurements (FTM) and inertial measurement unit (IMU) sensor data to associate the user detected on a camera footage with their corresponding smartphone identifier (e. g. WiFi MAC address).

Graph Matching Multimodal Association

Algorithms for bounding contribution for histogram estimation under user-level privacy

no code implementations7 Jun 2022 YuHan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser

In this scenario, the amount of noise injected into the histogram to obtain differential privacy is proportional to the maximum user contribution, which can be amplified by few outliers.

Federated Learning with Autotuned Communication-Efficient Secure Aggregation

no code implementations30 Nov 2019 Keith Bonawitz, Fariborz Salehi, Jakub Konečný, Brendan Mcmahan, Marco Gruteser

Federated Learning enables mobile devices to collaboratively learn a shared inference model while keeping all the training data on a user's device, decoupling the ability to do machine learning from the need to store the data in the cloud.

Federated Learning

Sub-6GHz Assisted MAC for Millimeter Wave Vehicular Communications

no code implementations7 Sep 2018 Baldomero Coll-Perales, Javier Gozalvez, Marco Gruteser

This paper contributes to this active research area by proposing a sub-6GHz assisted mmWave MAC that decouples the mmWave data and control planes.

Networking and Internet Architecture

Recognizing Textures with Mobile Cameras for Pedestrian Safety Applications

no code implementations1 Nov 2017 Shubham Jain, Marco Gruteser

Second, we aim at identifying when a distracted user is about to enter the street, which can be used to support safety functions such as warning the user to be cautious.

Material Recognition object-detection +1

Reading Between the Pixels: Photographic Steganography for Camera Display Messaging

no code implementations6 Apr 2016 Eric Wengrowski, Kristin Dana, Marco Gruteser, Narayan Mandayam

We sample from the resulting metamer sets to find color steps for each base color to embed a binary message into an arbitrary image with reduced visible artifacts.

Optimal Radiometric Calibration for Camera-Display Communication

no code implementations8 Jan 2015 Wenjia Yuan, Eric Wengrowski, Kristin J. Dana, Ashwin Ashok, Marco Gruteser, Narayan Mandayam

We present a novel method for communicating between a camera and display by embedding and recovering hidden and dynamic information within a displayed image.

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