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

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable.\udIn this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone\udvideo file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss\udaccuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified\ud1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as\ud0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds\udfrom both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time\udchange detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a\udsuccessful point cloud generation from smartphone images

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Accuracy assessment of building point clouds automatically generated from iphone images