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Using Bag of Visual Words and Spatial Pyramid Matching for Object Classification Along with Applications for RIS

机译:使用视觉单词袋和空间金字塔匹配进行对象分类以及RIS的应用

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Image analysis, classification and searching has been a perennial frontier in the domain of Computer Vision. Recent developments have shown significant improvement over the aspects of feature extraction, segmentation and image enhancement. With the proliferating rise in computational power, it is both attainable s as well as affordable to perform complex image transforms and computations in hand held devices, thereby making it possible to construct RIS based applications for everyday use. The paper presents a novel approach towards attaining user supplied image searching for online applications such as e-commerce and cloud using the popular Bag of Visual Key points 1 model and integrating spatial pyramid matching 2 . Such models need heavy data mining, strong datasets for training and accurate image feature extrapolation. The said approach aims at yielding a set of matching and homogeneous images for a given user supplied image.
机译:图像分析,分类和搜索已成为Computer Vision领域的常年前沿。最近的发展显示出在特征提取,分割和图像增强方面的显着改进。随着计算能力的迅速提高,在手持设备中执行复杂的图像转换和计算既可实现又可负担,从而使构建基于RIS的日常应用成为可能。本文提出了一种新颖的方法,该方法使用流行的Bag of Visual Key points 1模型和集成空间金字塔匹配2来实现用户提供的针对在线应用(例如电子商务和云)的图像搜索。这样的模型需要大量的数据挖掘,强大的数据集进行训练以及准确的图像特征外推。所述方法旨在针对给定的用户提供的图像产生一组匹配图像和同类图像。

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