Abstract
A unique problem is considered: how to automatically determine whether two images (pictures, drawings, or photos) show the same 3D object pictured in different views. Similarity or equality of the objects seen despite the spotting, size or angle of view is one of the biggest challenges. Thus, a unique proposition of solving this task is proposed. In this complex solution image sets are compared and following question is answered: are these sets similar in the sense that they present an object of the same type? The approach uses CNN-like deep neural networks for object region masking, specific feature extraction and proper type classification, and similarity measures for data matching. Experimental validation is performed on a public car image database.
The research work was supported by Warsaw University of Technology.
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Piwowarski, P., Kasprzak, W. (2021). Multi-stream Fusion in Image Sets Comparison. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2021: Recent Achievements in Automation, Robotics and Measurement Techniques. AUTOMATION 2021. Advances in Intelligent Systems and Computing, vol 1390. Springer, Cham. https://doi.org/10.1007/978-3-030-74893-7_22
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DOI: https://doi.org/10.1007/978-3-030-74893-7_22
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