Near-Online Tracking With Co-Occurrence Constraints in Blockchain-Based Edge Computing

【Author】 Sheng, Hao; Wang, Shuai; Zhang, Yang; Yu, Dongxiao; Cheng, Xiuzhen; Lyu, Weifeng; Xiong, Zhang

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】Multiobject tracking is a basic task in video analysis. Due to the strict requirements on efficiency and resource consumption, most of the applications on edge devices are online or near-online methods. Besides motion modeling, appearance information is also widely used for tracking. However, the influence of occlusion is usually ignored. In this article, spatial-temporal co-occurrence constraints (STCCs) features are introduced to resist occlusions by exploring the rich spatial and temporal information of tracklets. In addition, a novel blockchain-based near-online framework called co-occurrence constraints tracklet tracker (CoCTs) is proposed for cross-camera tracking. It inherits the advantages of the blockchain technology in sharing information. Based on blockchain, an efficient association mechanism and a reliable information sharing method are introduced. Experimental results show that CoCT performs high computational efficiency and low resource consumption. In the edge computing environment, it achieves real-time performance on cross-camera tracking. On the MOT17 benchmark, our method shows the state-of-the-art results compared with other online trackers.

【Keywords】Blockchain; Feature extraction; Trajectory; Internet of Things; Streaming media; Edge computing; Real-time systems; Blockchain; co-occurrence constraints; cross-edge; multi-object tracking; tracklet association

【发表时间】2021 44607

【收录时间】2022-01-02

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