A remote human activity detection system based on partial-fiber LDV and PTZ camera. (April 2019)

• Record Type: Journal Article
• Authors: Han, Xiyu; Lv, Tao; Wu, Shisong; Li, Yuanyang; He, Bin
• Is Part Of: Optics & laser technology. Volume 111(2019)
• Page Start: 575
• Page End: 584
• Publication Date: 2019-04
• Subjects: Laser Doppler Vibrometer -- Remote acoustic detection -- YOLO algorithm -- Multimodal detecting -- Voice enhancement; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2018.10.035
• Languages: English
• ISSNs: 0030-3992

Abstract

Highlights: A double-mode surveillance system is developed to detect remote human activities. A new LDV structure: partial-fiber structure is used to detect remote speech. A speech enhancement technique is applied to improve the quality of the voice. A YOLO algorithm is used to discriminate human target and surroundings. Abstract: To address the challenges of non-cooperative and remote human activity detection, a multimodal remote audio/video acquisition system is developed. The system mainly consists of a Pan-Tilt-Zoom (PTZ) camera and a Laser Doppler Virbometer (LDV). The traditional all-fiber structure has residual carriers, which degrades the system performance badly. To solve the problem, a partial-fiber LDV is developed to obtain remote audio by detecting the vibration of the object (caused by the acoustic pressure around the target). Besides, to improve the quality of LDV audio signals, a speech enhancement algorithm (OM-LSA) is applied to remove noises in the LDV audio signals. The PTZ camera can provide remote visual information. We also use the YOLO algorithm to discriminate human from the photos which are updated from the PTZ camera continuously. That is the primary application of the YOLO algorithm. Moreover, the YOLO algorithm is used to recognize the objects around the target person by processing the video signals acquired by PTZ camera, which can aid the LDV in finding a suitable vibration target. In experiments, we show that the remote (50 m) speech signals and visual signals can be obtained by this surveillance system. That means this system has the ability to detect remote human activities.