Back to Search
Start Over
Cost-Effective Ground-Moving Object Detection Method in Aerial Video by Change Detection of Delaunay Triangulation.
- Source :
- International Journal of Pattern Recognition & Artificial Intelligence; Jun2024, Vol. 38 Issue 8, p1-27, 27p
- Publication Year :
- 2024
-
Abstract
- This paper is dedicated to developing a cost-effective ground-moving object detection method in aerial videos. Without limitations on types, quantity, and distribution of moving objects, which were required by the previous methods, the proposed approach can detect various ground-moving objects in aerial videos captured through diverse flying states in various ground appearances. The proposed method is mainly composed of generation of the appropriate feature points, detection of moving objects, and target tracking. In the originality of our work, a novel detection strategy designed for ground-moving objects is based on change detection of Delaunay triangulation (CDDT) and a three-step motion vector search-based tracking algorithm is further exploited for enhancing the detection rate. Experimental results show that our method can achieve the detection rate of at least 95% (roughly similar to the famous existing state-of-the-art methods) and 0.03 second/frame (far less than the famous existing methods) using test videos (containing only several moving objects distributed in a sparse space) in the previous methods compared. Besides, the average detection rate of 86.81%, average false detection rate of 9.44%, and a frame rate of about 33 fps can be obtained using our test videos captured in the complicated ground appearances. This result makes the proposed method more attractive for detecting various ground-moving objects in aerial videos, when compared to other approaches, and can also achieve cost-effective performance. [ABSTRACT FROM AUTHOR]
- Subjects :
- TRACKING algorithms
TRIANGULATION
OBJECT tracking (Computer vision)
VIDEOS
Subjects
Details
- Language :
- English
- ISSN :
- 02180014
- Volume :
- 38
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- International Journal of Pattern Recognition & Artificial Intelligence
- Publication Type :
- Academic Journal
- Accession number :
- 178418336
- Full Text :
- https://doi.org/10.1142/S021800142455005X