A Temporal-Spatial Method for Group Detection, Locating and Tracking

IEEE Access

Houbing Song¹  Shengnan Li²  Zheng Qin² 

[1] Department of Electrical and Computer Engineering, West Virginia University, Montgomery, WV, USA;School of Software and TNList, Tsinghua University, Beijing, China;

关键词: Internet of Things;    group detection;    temporal-spatial;    smart computing;   

DOI  :  10.1109/ACCESS.2016.2600623

来源: DOAJ

【 摘 要 】

With the prevalence of smart devices, such as smart phones, wearable equipments, and infrastructures, location-based service (LBS) has thrived in our daily life. In those practical LBS applications, group detection and tracking is a context-related research field in many scenarios, such as school yard, office building, shopping mall and so on. In this paper, we heuristically develop a temporal-spatial method for clustering and locating the groups, and then leverage a CRF-based event detection mechanism to improve the performance of recognizing contextual behaviors. The experimental results demonstrate that our system can achieve an impressive accuracy and precision of grouping and tracking.

【 授权许可】

Unknown