Abstract: Exemplary embodiments are directed to biometric enrollment systems including a camera and an image analysis module. The camera configured is to capture a probe image of a subject, the probe image including an iris of the subject. The image analysis module is configured to determine an iris characteristic of the iris in the probe image. The image analysis module is configured to analyze the probe image relative to a first enrollment image to determine if a match exists based on the iris characteristic. If the match exists, the image analysis module is configured to electronically store the matched probe image as an accepted image. The image analysis module is configured to select and establish the accepted image as a second enrollment image if the accepted image meets enrollment image criteria.

Abstract: Exemplary embodiments are directed to biometric enrollment systems including a camera and an image analysis module. The camera configured is to capture a probe image of a subject, the probe image including an iris of the subject. The image analysis module is configured to determine an iris characteristic of the iris in the probe image. The image analysis module is configured to analyze the probe image relative to a first enrollment image to determine if a match exists based on the iris characteristic. If the match exists, the image analysis module is configured to electronically store the matched probe image as an accepted image. The image analysis module is configured to select and establish the accepted image as a second enrollment image if the accepted image meets enrollment image criteria.

Abstract: Exemplary embodiments are directed to biometric enrollment systems including a camera and an image analysis module. The camera configured is to capture a probe image of a subject, the probe image including an iris of the subject. The image analysis module is configured to determine an iris characteristic of the iris in the probe image. The image analysis module is configured to analyze the probe image relative to a first enrollment image to determine if a match exists based on the iris characteristic. If the match exists, the image analysis module is configured to electronically store the matched probe image as an accepted image. The image analysis module is configured to select and establish the accepted image as a second enrollment image if the accepted image meets enrollment image criteria.

Abstract: A method of capturing image data for iris code based identification of vertebrates, including humans, comprises the steps of: recording a digital image of an eye with a camera equipped with at least two light sources that have a fixed spatial relationship to an object lens of the camera; locating the eye in the digital image by detecting a specularity pattern that is created by reflection of light from said at least two light sources at a cornea of the eye; and calculating information on the position of the camera relative to the eye on the basis of said fixed spatial relationship between the light sources and the object lens and on the basis of said specularity pattern.

Abstract: A method of normalizing a digital image of an iris of an eye for the purpose of creating an iris code for identification of vertebrates, including humans, the method comprising the steps of: determining a pupil region in the image as a convex region having a boundary that can only be described by more than five independent parameters; determining, in the image, an outer boundary of the iris; and transforming an image of a ring shaped iris region that surrounds the pupil region into a coordinate system in which each point of the iris region is described by a first coordinate that indicates the position of the point along the boundary of the pupil and a second coordinate that indicates the distance of the point from said boundary, said second coordinate having a constant value when the point is located on the outer boundary of the iris.

Abstract: A method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of: deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value; forming a combined image by point-wise combining the intensity image with the texture image, identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.

Abstract: The present invention pertains to a method of generating a normalized digital image of an iris of an eye for the purpose of creating an iris code for identification of vertebrates, including humans, the method comprising the steps of: capturing one or more digital images of the eye with a camera; constructing a plurality of imaginary outer iris boundaries in the one or more digital images, based on a known dimension of the outer iris boundary of the eye of a given species of vertebrates; and using said imaginary boundaries for transforming the one or more digital images into a plurality of normalized iris image that are insensitive to variations in a dimension of a pupil of the eye.

Abstract: The present invention provides an improved method for estimating range of objects in images from various distances comprising receiving a set of images of the scene having multiple objects from at least one camera in motion. Due to the motion of the camera, each of the images are obtained at different camera locations. Then an object visible in multiple images is selected. Data related to approximate camera positions and orientations and the images of the visible object are used to estimate the location of the object relative to a reference coordinate system. Based on the computed data, a projected location of the visible object is computed and the orientation angle of the camera for each image is refined. Additionally, pairs of cameras with various locations can obtain dense stereo for regions of the image at various ranges.

Abstract: A method for detecting a moving target is disclosed that receives a plurality of images from at least one camera; receives a measurement of scale from one of a measurement device and a second camera; calculates the pose of the at least one camera over time based on the plurality of images and the measurement of scale; selects a reference image and an inspection image from the plurality of images of the at least one camera; and detects a moving target from the reference image and the inspection image based on the orientation of corresponding portions in the reference image and the inspection image relative to a location of an epipolar direction common to the reference image and the inspection image; and displays any detected moving target on a display. The measurement of scale can derived from a second camera or, for example, a wheel odometer.

Abstract: A method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of: deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value; forming a combined image by point-wise combining the intensity image with the texture image, identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.

Abstract: A method of normalizing a digital image of an iris of an eye for the purpose of creating an iris code for identification of vertebrates, including humans, the method comprising the steps of: determining a pupil region in the image as a convex region having a boundary that can only be described by more than five independent parameters; determining, in the image, an outer boundary of the iris; and transforming an image of a ring shaped iris region that surrounds the pupil region into a coordinate system in which each point of the iris region is described by a first coordinate that indicates the position of the point along the boundary of the pupil and a second coordinate that indicates the distance of the point from said boundary, said second coordinate having a constant value when the point is located on the outer boundary of the iris.

Abstract: The present invention pertains to a method of generating a normalized digital image of an iris of an eye for the purpose of creating an iris code for identification of vertebrates, including humans, the method comprising the steps of: capturing one or more digital images of the eye with a camera; constructing a plurality of imaginary outer iris boundaries in the one or more digital images, based on a known dimension of the outer iris boundary of the eye of a given species of vertebrates; and using said imaginary boundaries for transforming the one or more digital images into a plurality of normalized iris image that are insensitive to variations in a dimension of a pupil of the eye.

Abstract: A method of capturing image data for iris code based identification of vertebrates, including humans, comprises the steps of: recording a digital image of an eye with a camera equipped with at least two light sources that have a fixed spatial relationship to an object lens of the camera; locating the eye in the digital image by detecting a specularity pattern that is created by reflection of light from said at least two light sources at a cornea of the eye; and calculating information on the position of the camera relative to the eye on the basis of said fixed spatial relationship between the light sources and the object lens and on the basis of said specularity pattern.

Abstract: The present invention provides an improved method for estimating range of objects in images from various distances comprising receiving a set of images of the scene having multiple objects from at least one camera in motion. Due to the motion of the camera, each of the images are obtained at different camera locations. Then an object visible in multiple images is selected. Data related to approximate camera positions and orientations and the images of the visible object are used to estimate the location of the object relative to a reference coordinate system. Based on the computed data, a projected location of the visible object is computed and the orientation angle of the camera for each image is refined. Additionally, pairs of cameras with various locations can obtain dense stereo for regions of the image at various ranges.

Abstract: The present invention provides an improved system and method for estimating range of the objects in the images from various distances. The method comprises receiving a set of images of the scene having multiple objects from at least one camera in motion. Due to the motion of the camera, each of the images are obtained at different camera locations Then an object visible in multiple images is selected. Data related to approximate camera positions and orientations and the images of the visible object are used to estimate the location of the object relative to a reference coordinate system. Based on the computed data, a projected location of the visible object is computed and the orientation angle of the camera for each image is refined. Additionally, pairs of cameras with various locations can then be chosen to obtain dense stereo for regions of the image at various ranges.

Abstract: The present invention provides an improved system and method for estimating range of the objects in the images from various distances. The method comprises receiving a set of images of the scene having multiple objects from at least one camera in motion. Due to the motion of the camera, each of the images are obtained at different camera locations Then an object visible in multiple images is selected. Data related to approximate camera positions and orientations and the images of the visible object are used to estimate the location of the object relative to a reference coordinate system. Based on the computed data, a projected location of the visible object is computed and the orientation angle of the camera for each image is refined. Additionally, pairs of cameras with various locations can then be chosen to obtain dense stereo for regions of the image at various ranges.

Abstract: A method and concomitant apparatus for comprehensively representing video information in a manner facilitating indexing of the video information. Specifically, a method according to the inveniton comprises the steps of dividing a continuous video stream into a plurality of video scenes; and at least one of the steps of dividing, using intra-scene motion analysis, at least one of the plurality of scenes into one or more layers; representing, as a mosaic, at least one of the pluraliy of scenes; computing, for at least one layer or scene, one or more content-related appearance attributes; and storing, in a database, the content-related appearance attributes or said mosaic representations.

Abstract: The present invention is embodied in a method for representing and analyzing spatiotemporal data in order to make qualitative yet semantically meaningful distinctions among various regions of the data at an early processing stage. In one embodiment of the invention, successive frames of image data are analyzed to classify spatiotemporal regions as being stationary, exhibiting coherent motion, exhibiting incoherent motion, exhibiting scintillation and so lacking in structure as to not support further inference. The exemplary method includes filtering the image data in a spatiotemporal plane to identify regions that exhibit various spatiotemporal characteristics. The output data provided by these filters is then used to classify the data.

Abstract: A method and apparatus for accurately computing parallax information as captured by imagery of a scene. The method computes the parallax information of each point in an image by computing the parallax within windows that are offset with respect to the point for which the parallax is being computed. Additionally, parallax computations are performed over multiple frames of imagery to ensure accuracy of the parallax computation and to facilitate correction of occluded imagery.

Abstract: A method and apparatus for accurately computing parallax information as captured by imagery of a scene. The method computes the parallax information of each point in an image by computing the parallax within windows that are offset with respect to the point for which the parallax is being computed. Additionally, parallax computations are performed over multiple frames of imagery to ensure accuracy of the parallax computation and to facilitate correction of occluded imagery.