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

• Main Authors: Shengnan Li, Zheng Qin, Houbing Song
• Format: Article
• Language: English
• Published: IEEE 2016-01-01
• Series: IEEE Access
• Subjects: Internet of Things; group detection; temporal-spatial; smart computing
• Online Access: https://ieeexplore.ieee.org/document/7549033/

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.