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

Location determination finds wide applications in daily life. Instead ofexisting efforts devoted to localizing tourist photos captured by perspectivecameras, in this article, we focus on devising person positioning solutionsusing overhead fisheye cameras. Such solutions are advantageous in large fieldof view (FOV), low cost, anti-occlusion, and unaggressive work mode (withoutthe necessity of cameras carried by persons). However, related studies arequite scarce, due to the paucity of data. To stimulate research in thisexciting area, we present LOAF, the first large-scale overhead fisheye datasetfor person detection and localization. LOAF is built with many essentialfeatures, e.g., i) the data cover abundant diversities in scenes, human pose,density, and location; ii) it contains currently the largest number ofannotated pedestrian, i.e., 457K bounding boxes with groundtruth locationinformation; iii) the body-boxes are labeled as radius-aligned so as to fullyaddress the positioning challenge. To approach localization, we build a fisheyeperson detection network, which exploits the fisheye distortions by arotation-equivariant training strategy and predict radius-aligned human boxesend-to-end. Then, the actual locations of the detected persons are calculatedby a numerical solution on the fisheye model and camera altitude data.Extensive experiments on LOAF validate the superiority of our fisheye detectorw.r.t. previous methods, and show that our whole fisheye positioning solutionis able to locate all persons in FOV with an accuracy of 0.5 m, within 0.1 s.

Large-Scale Person Detection and Localization using Overhead Fisheye Cameras