Abstract
In the emergency rescue exercise of high-rise buildings, mastering the accurate position of the participants is an important means for coaches to arrange tactics, evaluate the efficiency of rescue aid, evaluate the effect and ensure the safety of the participants. Video location is a more accurate positioning method, using personnel detection, personnel tracking can lock the position of personnel in the monitoring, but once occlusive, personnel can not be detected, will cause the loss of personnel identity information, another problem is that the current technology is difficult to stably identify the identity of personnel through signs. Therefore, this paper studies the fusion algorithm based on the characteristics that the most widely used WiFi fingerprint location can provide rough position information and personnel identity information. The detection with identity information is obtained by matching the personnel information provided by the WiFi fingerprint location system with the detected personnel in the video. At the same time, the location result of WiFi fingerprint can provide reference position when occlusive for a long time. Aiming at the characteristics of fixed number of participants and fixed identity information in emergency rescue exercise, this paper proposes a personnel tracking algorithm based on appearance and motion characteristics. This algorithm reduces the incidence of identity exchange problem when the personnel are very close, and records the representation information of the participants for a long time, which can make the personnel can be rerecognized after a long period of disappearance, and avoid the problem of matching error caused by multiple matching of WiFi fingerprint information and video location information.
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Acknowledgement
This study was supported by State’s Key Project of Research and Development Plan (No. 2018YFC0810601, No. 2016YFC0901303). The work was conducted at University of Science and Technology Beijing.
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Ma, J., Shi, Z. (2019). Location and Fusion Algorithm of High-Rise Building Rescue Drill Scene Based on Binocular Vision. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1137. Springer, Singapore. https://doi.org/10.1007/978-981-15-1922-2_32
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DOI: https://doi.org/10.1007/978-981-15-1922-2_32
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