From Event: SPIE Optical Engineering + Applications, 2016
In the computer world, the consumption and generation of multimedia content are in constant growth due to the popularization of mobile devices and new communication technologies. Retrieve information from multimedia content to describe Mexican buildings is a challenging problem. Our objective is to determine patterns related to three building eras (Pre-Hispanic, colonial and modern). For this purpose, existing recognition systems need to process a plenty of videos and images. The automatic learning systems trains the recognition capability with a semantic-annotated database. We built the database taking into account high-level feature concepts, user knowledge and experience. The annotations helps correlating context and content to understand the data on multimedia files. Without a method, the user needs a super mind to remember all and registry this data manually. This article presents a methodology for a quick images annotation using a graphical interface and intuitive controls. Emphasizing in the most two important features: time-consuming during annotations task and the quality of selected images. Though, we only classify images by its era and its quality. Finally, we obtain a dataset of Mexican buildings preserving the contextual information with semantic-annotations for training and test of buildings recognition systems. Therefore, research on content low-level descriptors is other possible use for this dataset.
Abraham Montoya Obeso, Laura Mariel Amaya Reyes, Mario Lopez Rodriguez, Mario Humberto Mijes Cruz, Mireya Saraí García Vázquez, Jenny Benois-Pineau, Luis Miguel Zamudio Fuentes, Elizabeth Cano Martinez, Jesús Abimelek Flores Secundino, José Luis Rivera Martinez, and Alejandro Álvaro Ramírez Acosta, "Image annotation for Mexican buildings database," Proc. SPIE 9970, Optics and Photonics for Information Processing X, 99700Y (Presented at SPIE Optical Engineering + Applications: August 30, 2016; Published: 14 September 2016); https://doi.org/10.1117/12.2238352.
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