Abstract: A technique for classifying objects within an image is disclosed. In one embodiment, the technique is realized by identifying a portion of an image, and then filtering the portion of the image based upon an object characteristic and a reference within the image. The image can be a representation of a plurality of pixels, wherein at least some of the plurality of pixels are enabled to represent the identified portion of the image. The reference can be one of a reference plane or a terrain within the image.

Abstract: A technique for locating objects within an image is disclosed. In one embodiment, the technique is realized by obtaining an image and then identifying an object within the image based upon an orientation of the object within the image. The image can be a representation of a plurality of pixels, wherein the plurality of pixels are arranged in a plurality of columns and rows, and wherein at least some of the plurality of pixels are enabled to represent the object.

Abstract: A technique for tracking objects through a series of images is disclosed. In one embodiment, the technique is realized by obtaining at least first and second representations of a plurality of pixels, wherein at least one grouping of substantially adjacent pixels has been identified in each of the first and second representations. Each identified grouping of substantially adjacent pixels in the first representation is then matched with an identified grouping of substantially adjacent pixels in the second representation.

Abstract: A technique for disambiguating proximate objects within an image is disclosed. In one embodiment, the technique is realized by obtaining an image which is a representation of a plurality of pixels, wherein at least one grouping of substantially adjacent pixels has been identified in the plurality of pixels. Discontinuities are identified in each of the identified groupings of substantially adjacent pixels. Each of the identified groupings of substantially adjacent pixels are divided according to the identified discontinuities. It is then determined if each of the divided identified groupings of substantially adjacent pixels corresponds to an object to be classified.

Abstract: A technique for updating a background image is disclosed. In one embodiment, the technique is realized by obtaining at least two representations of an image. At least one portion of at least one of the at least two representations is identified. An updated representation of the image is then provided by averaging together the at least two representations excepting each identified portion.

Abstract: A technique for processing images is disclosed. In one embodiment, the technique is realized by obtaining a representation of an image, and then locating an area of interest in the representation. The located area of interest is then classified according to a first characteristic of one or more objects of interest and a reference within the image. If the located area of interest has been classified as an area containing at least one object of interest, the at least one object of interest can be disambiguated from other objects in the located area of interest.

Abstract: A technique for providing a computer generated face having coordinated eye and head movement is realized by providing a computer generated movable head and at least one computer generated movable eye. The movement of the computer generated movable head and the movement of the at least one computer generated movable eye are coordinated such that the movement of the computer generated movable head follows the movement of the at least one computer generated movable eye.

Abstract: A technique for acknowledging multiple objects using a computer generated face is realized by determining the location of at least two objects relative to a display device. A computer generated face is produced on the display device, wherein the computer generated face has at least one eye. The at least one eye is alternately directed between the at least two objects.