Bag of Words Model in Computer Vision (Paperback)

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. This is an article introducing the "Bag of words model" in computer vision, especially for object categorization. From now, the "BoW" model refers to the BoW model in computer vision unless explicitly declared. This technique is also known as "Bag of Features model." Before introducing the BoW model, the BoW in natural language processing is briefly reviewed. The BoW in NLP is a popular method for representing documents, which ignores the word orders. For example, "a good book" and "book good a" are the same under this model. The BoW model allows a dictionary-based modeling, and each document looks like a "bag," which contains some words from the dictionary. Computer vision researchers use a similar idea for image representation. For example, an image can be treated as a document, and features extracted from the image are considered as the "words." The BoW representation serves as the basic element for further processing, such as object categorization.