A genetic algorithm-based search method of camera deployment conditions for cooperative observation by AI
-
- MUKAI Tomohiro
- 北海道大学 大学院工学院
-
- YAGI Masahiro
- 北海道大学 大学院工学院
-
- TAKAHASHI Sho
- 北海道大学 大学院工学研究院
-
- HAGIWARA Toru
- 北海道大学 大学院工学研究院
Bibliographic Information
- Other Title
-
- AIによる協調観測のための遺伝的アルゴリズムに基づくカメラ配置条件の探索
Abstract
<p>The data obtained from various sensors is utilized for spatial analysis utilizing AI. To maximize the effectiveness of AI-based spatial analysis, it is necessary to estimate in advance factors such as the placement, installation angles, and quantity of multiple sensors. To make this possible, a search method for camera placement conditions based on iterative deepening depth-first search utilizing an evaluation function based on object detection results was constructed. However, there is a challenge of falling into local optima due to the limited search space. Therefore, in this paper, a search method for camera placement conditions based on genetic algorithms is proposed. Specifically, the solution obtained by the conventional method is used as the initial solution, and selection, crossover, and mutation are iteratively applied to explore camera placement conditions. This allows for searching broader search compared to conventional methods and achieves a method less prone to local optimal solution. The effectiveness of the proposed method is confirmed through experiments.</p>
Journal
-
- Artificial Intelligence and Data Science
-
Artificial Intelligence and Data Science 5 (1), 212-221, 2024
Japan Society of Civil Engineers
- Tweet
Details 詳細情報について
-
- CRID
- 1390581555878024960
-
- ISSN
- 24359262
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
-
- Abstract License Flag
- Disallowed