A Computer Vision Framework for Automatic Description of Indian Monuments

Pushkar Shukla, Beena Rautela, A. Mittal
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引用次数: 9

Abstract

Monument recognition and description has emerged as a promising area of research. For any given image of a monument a question arises that up to what extend can a computer model describe the monument from that image?The main objective of the paper is to propose a framework which is capable of identifying multiple attributes from a single image of a monument. Four different attributes i.e. the class of the monument, the style of the architecture, the time period in which the monument was constructed and the type of the monument are taken into consideration. The paper proposes a framework that relies on Deep Convolutional Neural Networks (DCNN) for describing the monument in terms of the aforementioned attributes. The experiments have been performed on a dataset comprising of 6102 images of 117 Indian monuments. The model was able to achieve an accuracy greater than 80% for all the different set of experimentations. The results clearly indicate the usefulness of the framework.
印度古迹自动描述的计算机视觉框架
monuments的识别与描述已成为一个很有前途的研究领域。对于任何给定的纪念碑图像,一个问题就出现了计算机模型能在多大程度上从图像中描述纪念碑?本文的主要目的是提出一个框架,该框架能够从单个纪念碑图像中识别多个属性。四个不同的属性,即纪念碑的类别,建筑风格,纪念碑建造的时期和纪念碑的类型被考虑在内。本文提出了一个基于深度卷积神经网络(DCNN)的框架,根据上述属性来描述纪念碑。实验是在一个包含117个印度纪念碑的6102张图像的数据集上进行的。对于所有不同的实验集,该模型都能达到80%以上的精度。结果清楚地表明了该框架的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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