Abstract
The present work proposes a real-time multi-object detection and tracking system to be implemented in commercial areas. The purpose is to gather and make sense of costumer behavior data extracted from surveillance footage (available from ceiling cameras) in order supply retailers with a set of analytics, management and planning tools to help them perform tasks such as planning demand and supply chains and organizing product placement on shelfs. To achieve this goal, deep learning techniques are used, which have been yielding outstanding results in computer vision problems in recent years.
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Baikova, D., Maia, R., Santos, P., Ferreira, J., Oliveira, J. (2019). Real Time Object Detection and Tracking. In: Novais, P., et al. Ambient Intelligence – Software and Applications –, 9th International Symposium on Ambient Intelligence. ISAmI2018 2018. Advances in Intelligent Systems and Computing, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-030-01746-0_15
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