دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
Semantic Riverscapes: Perception and evaluation of linear landscapes from oblique imagery using computer vision
ترجمه فارسی عنوان مقاله:
مناظر معنایی رودخانه: درک و ارزیابی مناظر خطی از تصاویر مایل با استفاده از بینایی کامپیوتری
منبع:
ScienceDirect- Elsevier- Landscape and Urban Planning, 228 (2022) 104569: doi:10:1016/j:landurbplan:2022:104569
نویسنده:
Junjie Luo
چکیده انگلیسی:
Traditional approaches for visual perception and evaluation of river landscapes adopt on-site surveys or as-
sessments through photographs. The former is expensive, hindering large-scale analyses, and it is conducted only
on street-level or top-down imagery. The latter only reflects the subjective perception and also entails a laborious
process. Addressing these challenges, this study proposes an alternative: a novel workflow for visual analysis of
urban river landscapes by combining unmanned aerial vehicle (UAV) oblique photography with computer vision
(CV) and virtual reality (VR). The approach is demonstrated with an experiment on a section of the Grand Canal
in China where UAV oblique panoramic imagery has been processed using semantic segmentation for visual
evaluation with an index system we designed. Concurrent surveys, immersive and non-immersive VR, are used to
evaluate these photos, with a total of 111 participants expressing their perceptions across multiple dimensions.
Then, the relationship between the people’s subjective visual perception and the river landscape environment as
seen by computers has been established. The results suggest that using this approach, rivers and surrounding
landscapes can be analyzed automatically and efficiently, and the mean pixel accuracy (MPA) of the developed
model is 90%, which advances state of the art. The results of this study can benefit urban planners in formulating
riverside development policies, analyzing the perception of plans for a future scenario before an area is rede-
veloped, and the method can also aid relevant parties in having a macro understanding of the overall situation of
the river as a basis for follow-up research. Due to simplicity, accuracy and effectiveness, this workflow is
transferable and cost-effective for large-scale investigations of riverscapes and linear heritage. We openly release
Semantic Riverscapes—the dataset we collected and processed, bridging another gap in the field.
keywords: ریورساید | باز کردن داده ها | GeoAI | بررسی های هوایی | هواپیماهای بدون سرنشین | واقعیت مجازی | Riverside | Open data | GeoAI | Aerial surveys | Drones | Virtual reality
قیمت: رایگان
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