Systems for automatically classifying images may be used in a wide variety of applications, including computer vision systems and media asset organization and retrieval systems. Many automatic classification systems classify images based at least in part on a content-based analysis of the images. In these systems, an image or a region of an image typically is represented by a set of low-level features (e.g., texture, color, and shape) that are extracted from the image. The images or image regions are classified by applying the corresponding features into a classifier, such as a Support Vector Machine, which has been trained on pre-labeled images or image regions in a target class (e.g., a human face class or a scene type class). Based on the input features, the classifier determines whether or not new image instances should be classified into the target type class.
In some content-based image retrieval approaches, low level visual features are used to group images into meaningful categories that, in turn, are used to generate indices for a database containing the images. In accordance with these approaches, images are represented by low level features, such as color, texture, shape, and layout. The features of a query image may be used to retrieve images in the databases that have similar features. In general, the results of automatic categorization and indexing of images improve when the features that are used to categorize and index the image more accurately capture the target aspects of the content of the images.
As individuals and organizations continue to rapidly accumulate large collections of image content, they increasingly will require systems and methods for organizing and browsing the image content in their collections. Although efforts have been made to detect and classify aspects (e.g., faces and eyes) of human subjects, little effort has been made to detect and classify aspects of nonhuman animals, such as dogs, cats, birds, and reptiles, which constitute a significant fraction of the image content that is captured and maintained in image databases. Accordingly, what are needed are systems and methods that are designed specifically to automatically classify pixels of nonhuman animals in images.