skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Do You See What I See? A Qualitative Study Eliciting High-Level Visualization Comprehension
Award ID(s):
2320920 2316496
PAR ID:
10533073
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
ACM CHI Conference on Human Factors in Computing Systems
Date Published:
ISBN:
9798400703300
Page Range / eLocation ID:
1 to 26
Format(s):
Medium: X
Location:
Honolulu HI USA
Sponsoring Org:
National Science Foundation
More Like this
  1. To accelerate electrons to multi-GeV energies with lasers, keep the bright light tight. 
    more » « less
  2. Neural Radiance Fields (NeRFs) have been remarkably successful at synthesizing novel views of 3D scenes by optimizing a volumetric scene function. This scene function models how optical rays bring color information from a 3D object to the camera pixels. Radio frequency (RF) or audio signals can also be viewed as a vehicle for delivering information about the environment to a sensor. However, unlike camera pixels, an RF/audio sensor receives a mixture of signals that contain many environmental reflections (also called “multipath”). Is it still possible to infer the environment using such multipath signals? We show that with redesign, NeRFs can be taught to learn from multipath signals, and thereby “see” the environment. As a grounding application, we aim to infer the indoor floorplan of a home from sparse WiFi measurements made at multiple locations inside the home. Although a difficult inverse problem, our implicitly learnt floorplans look promising, and enables forward applications, such as indoor signal prediction and basic ray tracing. 
    more » « less