English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

To help improve the safety and accessibility of indoor spaces, researchersand health professionals have created assessment instruments that enablehomeowners and trained experts to audit and improve homes. With advances incomputer vision, augmented reality (AR), and mobile sensors, new approaches arenow possible. We introduce RASSAR (Room Accessibility and Safety Scanning inAugmented Reality), a new proof-of-concept prototype for semi-automaticallyidentifying, categorizing, and localizing indoor accessibility and safetyissues using LiDAR + camera data, machine learning, and AR. We present anoverview of the current RASSAR prototype and a preliminary evaluation in asingle home.

Towards Semi-automatic Detection and Localization of Indoor Accessibility Issues using Mobile Depth Scanning and Computer Vision