Object Categorization From Image Search

In computer vision, the problem of object categorization from image search is the problem of training a classifier to recognize categories of objects, using only the images retrieved automatically with an Internet search engine. Ideally, automatic image collection would allow classifiers to be trained with nothing but the category names as input. This problem is closely related to that of content-based image retrieval (CBIR), where the goal is to return better image search results rather than training a classifier for image recognition.

Traditionally, classifiers are trained using sets of images that are labeled by hand. Collecting such a set of images is often a very time-consuming and laborious process. The use of Internet search engines to automate the process of acquiring large sets of labeled images has been described as a potential way of greatly facilitating computer vision research.

Read more about Object Categorization From Image SearchPLSA Approach, OPTIMOL, Object Categorization in Content-based Image Retrieval

Other articles related to "object categorization from image search, image, images, search, image search":

Object Categorization From Image Search - Object Categorization in Content-based Image Retrieval
... Typically, image searches only make use of text associated with images ... The problem of content-based image retrieval is that of improving search results by taking into account visual information contained in the images themselves ... methods make use of classifiers trained on image search results, to refine the search ...

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