期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2013
卷号：10
期号：4
出版社：IJCSI Press
摘要：Scene classification and object recognition is a hot area of research in the field of computer vision and has always fascinated researchers to explore strategies for optimization of results. Global and local features are manipulated to find a match in the images or scene categories.This paper mainly comprises of finding the scene labels based on the objects present in it.The image is transformed into a feature space and the classifier is trained to differentiate each class in the feature space.Various feature extraction techniques like RGB histogram , SIFT and co-variance are explored in this paper to find an optimized result. Different classifiers were tested individually as well as their combinations to achieve better results. Combination of Sparse SIFT and Dense SIFT techniques was found to perform better compared to others.
关键词：Scene Classification; object recognition; Bag ofwords; Sparse SIFT; Dense SIFT.
