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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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DTSTART:18871231T000000
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DTSTAMP:20250110T023313Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241206T105600
DTEND;TZID=Asia/Tokyo:20241206T110800
UID:siggraphasia_SIGGRAPH Asia 2024_sess142_papers_408@linklings.com
SUMMARY:Large Scale Farm Scene Modeling from Remote Sensing Imagery
DESCRIPTION:Technical Papers\n\nZhiqi Xiao and Hao Jiang (Institute of Com
 puting Technology, Chinese Academy of Sciences; University of Chinese Acad
 emy of Sciences); Zhigang Deng (University of Houston); and Ran Li, Wenwei
  Han, and Zhaoqi Wang (Institute of Computing Technology, Chinese Academy 
 of Sciences; University of Chinese Academy of Sciences)\n\nIn this paper w
 e propose a scalable framework for large-scale farm scene modeling that ut
 ilizes remote sensing data, specifically satellite images. Our approach be
 gins by accurately extracting and categorizing the distributions of variou
 s scene elements from satellite images into four distinct layers: fields, 
 trees, roads, and grasslands. For each layer, we introduce a set of contro
 llable Parametric Layout Models (PLMs). These models are capable of learni
 ng layout parameters from satellite images, enabling them to generate comp
 lex, large-scale farm scenes that closely reproduce reality across multipl
 e scales. Additionally, our framework provides intuitive control for users
  to adjust layout parameters to simulate different stages of crop growth a
 nd planting patterns. This adaptability makes our model an excellent tool 
 for graphics and virtual reality applications. Experimental results demons
 trate that our approach can rapidly generate a variety of realistic and hi
 ghly detailed farm scenes with minimal inputs.\n\nRegistration Category: F
 ull Access, Full Access Supporter\n\nLanguage Format: English Language\n\n
 Session Chair: Maria Larsson (University of Tokyo)
URL:https://asia.siggraph.org/2024/program/?id=papers_408&sess=sess142
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