Content-based image retrieval

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Context of the project within the fieldThe goal of researchers in computer vision is to build a general-purpose computer vision system that can "see" in a fashion comparable to humans. The impact of such an advance on society stands to rival the digital revolution brought about by the general-purpose computer. Unfortunately, this task has proven to be extremely challenging. Much of the difficulty revolves around the ability to create computer programs that can analyze digital images to both detect and identify man-made and natural objects that are set against an unknown visual background. The task is difficult since objects may appear at many spatial locations and scales in the image, the image background can be virtually anything, and there is often a very large visual variation in what constitutes the elements of a particular class.This proposal addresses two related, but different problems in computer vision: 1. Specific object recognition; 2. Generic object class detection. Specific object recognition makes use of a priori knowledge (training data) of a single object's features in order to simplify the task of determining the exact identity of a man-made or natural object in an image. An example is identifying a particular person's face. By contrast, the goal of a generic object class detection system is to (i) find and (ii) determine the class identity or category of the objects in an image. An example is finding all faces in a graduating class image. In this case, spatial localization in the image is required, as well as possibly the pose (in 2D or 3D) and size of the object.The long-term objective of this proposal is to solve what used to be called the image understanding or scene analysis problem. That is, create a computer program that understands a scene, and by extension, describe and explain it. From a more practical point of view, two long-term scenarios are contemplated. One is to develop a program that can automatically search the Web for images of specific objects or object classes. The second is the creation of an intelligent visual machine that is capable of seriously interacting with the human environment. Perhaps the first is more realistic than the second.