9 December 2015 Object recognition based on Google's reverse image search and image similarity
Author Affiliations +
Proceedings Volume 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015); 98170Q (2015) https://doi.org/10.1117/12.2228505
Event: Seventh International Conference on Graphic and Image Processing, 2015, Singapore, Singapore
Abstract
Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
András Horváth, "Object recognition based on Google's reverse image search and image similarity", Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170Q (9 December 2015); doi: 10.1117/12.2228505; https://doi.org/10.1117/12.2228505
PROCEEDINGS
5 PAGES


SHARE
RELATED CONTENT


Back to Top