Trainable Agents Movement Strategies for Advertising Sign Visual Descriptors

We provide a complete description of our investigation into specialized visual descriptors application as a part of combined classifier architecture for advertising signboards photographs classification problem. We propose novel types of descriptors (pure convolutional neural networks based and base...

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Bibliographic Details
Published in:Pattern recognition and image analysis 2022-09, Vol.32 (3), p.651-657
Main Authors: Samarin, A., Savelev, A., Toropov, A., Dzestelova, A., Malykh, V., Mikhailova, E., Motyko, A.
Format: Article
Language:English
Subjects:
Advertising
Artificial neural networks
Commercial buildings
Computer Science
Fonts
Image Processing and Computer Vision
Pattern Recognition
SELECTED PAPERS OF THE 8th INTERNATIONAL WORKSHOP “IMAGE MINING. THEORY AND APPLICATIONS”
Semantics
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Summary:We provide a complete description of our investigation into specialized visual descriptors application as a part of combined classifier architecture for advertising signboards photographs classification problem. We propose novel types of descriptors (pure convolutional neural networks based and based on trainable parametrized agent movement strategies) showing the state of the art results in the extraction of visual characteristics and related semantics of text fonts presented on a sign. To provide comparisons of developed approaches and its effectiveness examination, we used two datasets of commercial building facade photographs grouped by the type of presented business.
ISSN:1054-6618
1555-6212
DOI:10.1134/S1054661822030373