Abstract
One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising panels. For such a purpose, a previous stage is to accurately detect and locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based on a deep neural network architecture that minimizes the number of false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection over Union (IoU) accuracy metric make this proposal applicable in real complex urban images.
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Acknowledgments
The authors gratefully acknowledge the financial support of the CYTED Network “Ibero-American Thematic Network on ICT Applications for Smart Cities” (Ref: 518RT0559) and the Spanish MICINN RTI Project (Ref: RTI2018-098019-B-100). The third author acknowledge the support of the ESPOL project PRAIM (FIEC-09-2015), the Spanish MICINN Project TIN2017-89723-P and “CERCA Programme/Generalitat de Catalunya”.
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Morera, Á., Sánchez, Á., Sappa, Á.D., Vélez, J.F. (2019). Robust Detection of Outdoor Urban Advertising Panels in Static Images. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_21
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DOI: https://doi.org/10.1007/978-3-030-24299-2_21
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