Abstract: This invention is a system and method to perform categorization (classification) of multimedia items. These items are comprised of a multitude of disparate information sources, in particular, visual information and textual information. Classifiers are induced based on combining textual and visual feature vectors. Textual features are the traditional ones, such as, word count vectors. Visual features include, but are not limited to, color properties of key intervals and motion properties of key intervals. The visual feature vectors are determined in such a fashion that the vectors are sparse. The vector components are features such as the absence or presence of the color green in spatial regions and the absence or the amount of visual flow in spatial regions of the media items. The text and the visual representation vectors are combined in a systematic and coherent fashion. This vector representation of a media item lends itself to well-established learning techniques.

Abstract: A system and method for automatic detecting neutral expressionless faces in digital images and video is described. First a face detector is used to detect the pose and position of a face and find the facial components. Second, the detected face is normalized to a standard size face. Then a set of geometrical facial features and three histograms in zones of mouth are extracted. Finally, by feeding these features to a classifier, the system detects if there is the neutral expressionless face or not.

Abstract: A system and method for multi-party authentication is described. The multi-party authentication process uses synchronous and persistent biometrics signals received from parties to a transaction, based on a policy, to approve a transaction request. The biometrics signals preferably are expressed as compressed video signals having steganographically inserted challenge response data. Several business applications are described that are based on the multi-party authentication engine.

Abstract: An image processing system segments an object from the background of a scene where the scene is illuminated by unknown ambient light sources. An image of the scene with the object and an image of the background scene are captured by an image input device. These images are color corrected, using the image of a gray patch that is visible. A further transform converts the image from a red, green, blue format into a hue, saturation and intensity representation. The two images are then novelly compared on a pixel-by-pixel basis in the hue, saturation and intensity domain.

Abstract: The system and method obscures descriptive image information about one or more images. The system comprises a selector for selecting the descriptive image information from one or more of the images, a transformer that transforms the descriptive information into a transformed state, and an authorizer that provides authorization criteria with the image. In a preferred embodiment, the transformed state is the respective image encoded with the descriptive information. The descriptive information can be obscured so that the descriptive information in the transformed state can be decoded only if one or more authorization inputs satisfy the authorization criteria.

Abstract: A system and method for automatic detecting neutral expressionless faces in digital images and video is described. First a face detector is used to detect the pose and position of a face and find the facial components. Second, the detected face is normalized to a standard size face. Then a set of geometrical facial features and three histograms in zones of mouth are extracted. Finally, by feeding these features to a classifier, the system detects if there is the neutral expressionless face or not.

Abstract: This invention is a system and method to perform categorization (classification) of multimedia items. These items are comprised of a multitude of disparate information sources, in particular, visual information and textual information. Classifiers are induced based on combining textual and visual feature vectors. Textual features are the traditional ones, such as, word count vectors. Visual features include, but are not limited to, color properties of key intervals and motion properties of key intervals. The visual feature vectors are determined in such a fashion that the vectors are sparse. The vector components are features such as the absence or presence of the color green in spatial regions and the absence or the amount of visual flow in spatial regions of the media items. The text and the visual representation vectors are combined in a systematic and coherent fashion. This vector representation of a media item lends itself to well-established learning techniques.

Abstract: This invention is a business system and method to perform categorization (classification) of multimedia items and to make business decisions based on the categorization of the item. The multimedia items are comprised of a multitude of disparate information sources, in particular, visual information and textual information. Classifiers are induced based on combining textual and visual feature vectors. Textual features are the traditional ones. Visual features include, but are not limited to, color properties of key intervals and motion properties of key intervals. The visual feature vectors are determined in such a fashion that the vectors are sparse. The text and the visual representation vectors are combined in a systematic and coherent fashion. This vector representation of a media item lends itself to well-established learning techniques and can be used for multimedia item categorization. The resulting business system, subject of this invention, can be used for many purposes.

Abstract: In an automatic fingerprint authentication or identification system, the fingerprint image acquisition is severely effected by the limitations of the acquisition process. The two modes of input, viz. scanning inked fingerprints from paper records or directly from a finger using live-scan fingerprint scanners suffer from the following noise sources in the input in addition to standard noise in the camera. Non-uniform ink application, uneven pressure while rolling on the paper or pressing on the scanner surface and external dirt like oil and climatic variations in the moisture content of skin are some of the main causes for the ridges and valleys not to be imaged clearly. This invention deals with a method of learning a set of partitioned least-sqaures filters that can be derived from a given set of images and ground truth pairs as an offline process. The learned filters are convolved with input fingerprint images to obtain the enhanced image.

Abstract: A business method for using computer image processing for selectable task-based digital video compression is described. The method is intended to reduce travel of experts and let these experts direct field agents in performing tasks remotely. The tasks to be performed in the remote field can be monitoring, manipulating, and navigating. A field agent performs the manipulation and navigation operations, this agent can be a human being or a robot. The task-based compression algorithms use computer vision techniques to extract the bare minimum amount of information from the remote field scenery to allow the task to be performed. High frame rate photo-realistic reconstruction of the remote scene is not generally necessary.

Abstract: A system and method for using computer image processing for selectable task-based digital video compression is described. The system is intended to reduce travel of experts and let these experts direct field agents in performing tasks remotely. The tasks to be performed in the remote field can be monitoring, manipulating, and navigating. A field agent performs the manipulation and navigation operations, this agent can be a human being or a robot. The task-based compression algorithms use computer vision techniques to extract the bare minimum amount of information from the remote field scenery to allow the task to be performed. High frame rate photo-realistic reconstruction of the remote scene is not generally necessary.

Abstract: A system and method use computer image processing for setting the parameters for an image acquisition device of a camera. The image parameters are set automatically by analyzing the image to be taken, and setting the controls according to the subject matter, in the same manner as an expert photographer would be able to. The system can run in a fully automatic mode choosing the best image parameters, or a “guided mode” where the user is prompted with choices where a number of alternate settings would be reasonable.

Abstract: An image processing system segments an object from the background of a scene by controlling a light source to illuminate the object more in one scene image than in another scene image. The two scene images are captured by an image input device and are then compared. The part of the image that experienced an increase in intensity is segmented as corresponding to the object. The image input device and the light source can also be placed in an opaque enclosure with an opening through which the input device can view and the light can illuminate the object. By placing the enclosure the correct distance away from the object, the effects of ambient light on the image are removed. Object glare is removed by a polarizing filter system.

Abstract: The present system and apparatus uses image processing to recognize objects within a scene. The system includes an illumination source for illuminating the scene. By controlling the illumination source, an image processing system can take a first digitize image of the scene with the object illuminated a higher level and a second digitized image with the object illuminated at a lower level. Using an algorithm, the object(s) image is segmented from a background image of the scene by a comparison of the two digitized images taken. A processed image (that can be used to characterize features) of the object(s) is then compared to stored reference images. The object is recognized when a match occurs. The system can recognize objects independent of size and number and can be trained to recognize objects that is was not originally programmed to recognize.