Study of BoF Model Based Image Representation
Ye Liang · 2014
Designing a suitable image representation is one of the most fundamental issues of computer vision.BoF model is very popular and used extensively in image classification,video search,robot localization and texture recognition.BoF feature is an orderless collection of quantized local image descriptors.While this feature representation discards structural and spatial information,BoF model is conceptually and computationally simple,even as good as stateof-theart methods.Three steps in the popular BoF were studied in detail,including feature extraction,feature coding and feature pooling.In the end,the main problems and challenges were highlighted based on analysis of current research technique.