Abstract
In this paper, we propose a 3D model-based food traceability information extraction method for processing video surveillance data. The proposed method first builds a 3D model of the surveillance area. Then, the video cameras are mapped in the 3D model and the coordinate transform functions from the 2D camera coordinates to the 3D model coordinates are calculated. Next, the object detection method is applied to identify the target which is then mapped into the 3D coordinates so that its 3D trajectory can be generated. Finally, we merge multiple trajectories from different cameras to create the complete traceability information for the target object. According to the experimental results, the proposed method can efficiently extract useful traceability information for a video surveillance system.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 41201486), the National Key Technologies R&D Program of China (Grant No. 2013BAH16F 2015BAD18B02 and 2015BAK36B02), and the project of the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) in the Collaborative Innovation Center of Modern Grain Circulation and Security, Nanjing University of Finance and Economics.
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Mao, B., He, J., Cao, J., Bigger, S., Vasiljevic, T. (2015). 3D Model-Based Food Traceability Information Extraction Framework. In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_16
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DOI: https://doi.org/10.1007/978-3-319-24474-7_16
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