Abstract: In a method, computer program, and system a dental target, such as a tooth, is located within a digital dental image. A reference object that was placed in the patient's mouth is segmented within a digital dental image to provide a segmented reference. The reference object has a predetermined size dimension. A window is segmented in the dental image at the position of the dental target. The segmented reference defines the relative size and location of the window, prior to the segmenting of the window.

Abstract: A method of finding an object in an image that consists of describing an object shape by one or more sets of feature points (220); estimating positions of the feature points (310); finding new locations for each feature point based on an appearance model of an aggregate appearance of the object in local neighborhoods of all features points (320); and constraining the positions of the feature points based on a shape model (330).

Abstract: In a method, computer program, and system a dental target, such as a tooth, is located within a digital dental image. A reference object that was placed in the patient's mouth is segmented within a digital dental image to provide a segmented reference. The reference object has a predetermined size dimension. A window is segmented in the dental image at the position of the dental target. The segmented reference defines the relative size and location of the window, prior to the segmenting of the window.

Abstract: In a method, computer program, and system a dental target, such as a tooth, is located within a digital dental image. A reference object that was placed in the patient's mouth is segmented within a digital dental image to provide a segmented reference. The reference object has a predetermined size dimension. A window is segmented in the dental image at the position of the dental target. The segmented reference defines the relative size and location of the window, prior to the segmenting of the window.

Abstract: A method of finding an object in an image that consists of describing an object shape by one or more sets of feature points (220); estimating positions of the feature points (310); finding new locations for each feature point based on an appearance model of an aggregate appearance of the object in local neighborhoods of all features points (320); and constraining the positions of the feature points based on a shape model (330).

Abstract: A digital image processing method detects facial features in a digital image. This method includes the steps of detecting iris pixels in the image, clustering the iris pixels, and selecting at least one of the following schemes to identify eye positions: applying geometric reasoning to detect eye positions using the iris pixel clusters; applying a summation of squared difference method using the iris pixel clusters to detect eye positions; and applying a summation of squared difference method to detect eye positions from the pixels in the image. The method applied to identify eye positions is selected on the basis of the number of iris pixel clusters, and the facial features are located using the identified eye positions.

Abstract: A retouching method for enhancing an appearance of a face located in a digital image involves acquiring a digital image containing one or more faces and detecting a location of facial feature points in the faces, where the facial feature points include points identifying salient features such as skin, eyes, eyebrows, nose, mouth, and hair. The location of the facial feature points are used to segment the face into different regions such as skin, eyes, eyebrows, nose, mouth, neck and hair regions. Facially relevant characteristics of the different regions are determined and, based on these facially relevant characteristics, an ensemble of enhancement filters are selected, each customized especially for a particular region, and the default parameters for the enhancement filters are selected. The enhancement filters are then executed on the particular regions, thereby producing an enhanced digital image from the digital image.

Abstract: A digital image processing method detects facial features in a digital image. This method includes the steps of detecting iris pixels in the image, clustering the iris pixels, and selecting at least one of the following schemes to identify eye positions: applying geometric reasoning to detect eye positions using the iris pixel clusters; applying a summation of squared difference method using the iris pixel clusters to detect eye positions; and applying a summation of squared difference method to detect eye positions from the pixels in the image. The method applied to identify eye positions is selected on the basis of the number of iris pixel clusters, and the facial features are located using the identified eye positions.

Abstract: A three-dimensional model of a scene is obtained from a plurality of three-dimensional panoramic images of a scene, wherein each three-dimensional panoramic image is derived from a plurality of range images captured from a distinct spatial position. Transformations are determined that align the plurality of three-dimensional panoramic images, and spatial information is integrated from the plurality of three-dimensional panoramic images to form a spatial three-dimensional model of the scene. Finally, intensity and texture information is integrated from the plurality of three-dimensional panoramic images onto the spatial three-dimensional model to form a three-dimensional model of the scene containing both spatial and intensity information.

Abstract: A retouching method for enhancing an appearance of a face located in a digital image involves acquiring a digital image containing one or more faces and detecting a location of facial feature points in the faces, where the facial feature points include points identifying salient features such as skin, eyes, eyebrows, nose, mouth, and hair. The location of the facial feature points are used to segment the face into different regions such as skin, eyes, eyebrows, nose, mouth, neck and hair regions. Facially relevant characteristics of the different regions are determined and, based on these facially relevant characteristics, an ensemble of enhancement filters are selected, each customized especially for a particular region, and the default parameters for the enhancement filters are selected. The enhancement filters are then executed on the particular regions, thereby producing an enhanced digital image from the digital image.

Abstract: A three-dimensional model of a scene is obtained from a plurality of three-dimensional panoramic images of a scene, wherein each three-dimensional panoramic image is derived from a plurality of range images captured from a distinct spatial position. Transformations are determined that align the plurality of three-dimensional panoramic images, and spatial information is integrated from the plurality of three-dimensional panoramic images to form a spatial three-dimensional model of the scene. Finally, intensity and texture information is integrated from the plurality of three-dimensional panoramic images onto the spatial three-dimensional model to form a three-dimensional model of the scene containing both spatial and intensity information.

Abstract: A digital image processing method detects facial features in a digital image. This method includes the steps of detecting iris pixels in the image, clustering the iris pixels, and selecting at least one of the following schemes to identify eye positions: applying geometric reasoning to detect eye positions using the iris pixel clusters; applying a summation of squared difference method using the iris pixel clusters to detect eye positions; and applying a summation of squared difference method to detect eye positions from the pixels in the image. The method applied to identify eye positions is selected on the basis of the number of iris pixel clusters, and the facial features are located using the identified eye positions.

Abstract: A method of producing an animated electronic message in which at least a portion of a fee associated with producing the animated electronic message is paid for by a sponsor. The method comprises the steps of a user accessing a database which includes at least one sponsor message and software for producing the animated electronic message; the user using the software to produce the animated electronic message; the user agreeing to use the sponsor message which will provide a credit for some of the fee for producing the animated electronic message; and attaching the sponsor message and the animated electronic message which is sent to one or more recipients. In a further embodiment, a sponsor coupon is distributed with the sponsor message and the animated message. In a still further embodiment, the sponsor message is animated. In yet a further embodiment, the credit for some of the fee is paid by the sponsor to a service provider or to the user.