Abstract
This paper proposes the use of smart 360-degree cameras for activity monitoring. By exploiting the geometric properties of these cameras and adopting off-the-shelf tracking algorithms adapted to equirectangular images, this paper shows how simple it becomes deploying a camera network, and detecting the presence of pedestrians in predefined regions of interest with minimal information on the camera, namely its height. The paper further shows that smart 360-degree cameras can enhance motion understanding in the environment and proposes a simple method to estimate the heatmap of the scene to highlight regions where pedestrians are more often present. Quantitative and qualitative results demonstrate the effectiveness of the proposed approach.
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Acknowledgement
This work was partially supported by the Italian MIUR within PRIN 2017, Project Grant 20172BH297_004: I-MALL - improving the customer experience in stores by intelligent computer vision.
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Lo Presti, L., Mazzola, G., La Cascia, M. (2023). Activity Monitoring Made Easier by Smart 360-degree Cameras. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13806. Springer, Cham. https://doi.org/10.1007/978-3-031-25075-0_20
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