Flow-pose Net: an effective two-stream network for fall detection

• Published in: The Visual computer Vol. 39; no. 6; pp. 2305 - 2320
• Main Authors: Fei, Kexin, Wang, Chao, Zhang, Jiaxu, Liu, Yuanzhong, Xie, Xing, Tu, Zhigang
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023; Springer Nature B.V
• Subjects: Accuracy; Artificial Intelligence; Background noise; Cameras; Computer Graphics; Computer Science; Deep learning; Design; Fall detection; Feature extraction; Human mechanics; Human motion; Image Processing and Computer Vision; Machine learning; Neural networks; Optical flow (image analysis); Original Article; Pose estimation; Sensors; Video; Flow-pose Net; Human pose; Simultaneous motion and appearance feature extraction; Fall detection; Optical flow

Aging society gives rise to the need of fall detection for the elderly. The interference of the environmental noise and the loss of motion information causing fall detection still challenging. In this work, we present a novel two-stream network, called Flow-pose Net (FP-Net), which integrates the op...