DBF-YOLO: a fall detection algorithm for complex scenes

In complex environments, factors such as varying light intensities, occluded body shapes, crowding, and significant changes in target scale result in low accuracy, reduced detection efficiency, and frequent missed detections in human fall detection. This paper proposes an optimized version of YOLOv8...

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Bibliographic Details
Published in:	Signal, image and video processing Vol. 19; no. 7; p. 532
Main Authors:	Wang, Xu, Xiang, Xiaodong
Format:	Journal Article
Language:	English
Published:	London Springer London 01.07.2025 Springer Nature B.V
Subjects:	Accuracy Algorithms Computer Imaging Computer Science Computer vision Deep learning Design Efficiency Fall detection Feature extraction Formability Image Processing and Computer Vision Luminous intensity Methods Modules Multimedia Information Systems Object recognition Original Paper Pattern Recognition and Graphics Posture Real time Sensors Signal,Image and Speech Processing Vision Wearable computers Complex scenes Focal EIoU Fall detection Deformable convolution BiFPN
ISSN:	1863-1703, 1863-1711
Online Access:	Get full text
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