Abstract:
A method and system to determine the disparity associated with one or more textured regions of a plurality of images is presented. The method comprises the steps of breaking up the texture into its color primitives, further segmenting the textured object into any number of objects comprising such primitives, and then calculating a disparity of these objects. The textured objects emerge in the disparity domain, after having their disparity calculated. Accordingly, the method is further comprised of defining one or more textured regions in a first of a plurality of images, determining a corresponding one or more textured regions in a second of the plurality of images, segmenting the textured regions into their color primitives, and calculating a disparity between the first and second of the plurality of images in accordance with the segmented color primitives.
Abstract:
A method and system for generating a disparity map. The method comprises the steps of generating a first disparity map based upon a first image and a second image acquired at a first time, acquiring at least a third image and a fourth image at a second time, and determining one or more portions comprising a difference between one of the first and second images and a corresponding one of the third and fourth images. A disparity map update is generated for the one or more determined portions, and a disparity map is generated based upon the third image and the fourth image by combining the disparity map update and the first disparity map.
Abstract:
A method and system to determine the disparity associated with one or more textured regions of a plurality of images is presented. The method comprises the steps of breaking up the texture into its color primitives, further segmenting the textured object into any number of objects comprising such primitives, and then calculating a disparity of these objects. The textured objects emerge in the disparity domain, after having their disparity calculated. Accordingly, the method is further comprised of defining one or more textured regions in a first of a plurality of images, determining a corresponding one or more textured regions in a second of the plurality of images, segmenting the textured regions into their color primitives, and calculating a disparity between the first and second of the plurality of images in accordance with the segmented color primitives.
Abstract:
A method and system for calibrating a lens. The method includes defining a plurality of omni-symmetrical regions within the lens, determining one or more localized lens parameters associated with each of the plurality of omni-symmetrical regions, and defining a localized set of calibration parameters for each of the plurality of omni-symmetrical region. The localized set of calibration parameters may then be employed in a computational image application.
Abstract:
Multiview calibration is essential for accurate three-dimensional computation. However, multiview calibration can not be accurate enough because of the tolerances required in some of the intrinsic and extrinsic parameters that are associated with the calibration process, along with fundamental imperfections that are associated with the manufacturing and assembly process itself. As a result, residual error in calibration is left over, with no known methods to mitigate such errors. Residual error mitigation is presented in this work to address the shortcomings that are associated with calibration of multiview camera systems. Residual error mitigation may be performed inline with a given calibration approach, or may be presented as a secondary processing step that is more application specific. Residual error mitigation aims at modifying the original parameters that have been estimated during an initial calibration process. These new, modified parameters are then used for triangulation and depth estimation of scene information. This approach also resolves parameter tolerances that are either too cumbersome to measure, or otherwise impossible to measure for practical stereo and multiview camera production and calibration applications.
Abstract:
A method and system for calibrating a lens. The method includes defining a plurality of omni-symmetrical regions within the lens, determining one or more localized lens parameters associated with each of the plurality of omni-symmetrical regions, and defining a localized set of calibration parameters for each of the plurality of omni-symmetrical region. The localized set of calibration parameters may then be employed in a computational image application.
Abstract:
A method and apparatus for segmenting an image are provided. The method may include the steps of clustering pixels from one of a plurality of images into one or more segments, determining one or more unstable segments changing by more than a predetermined threshold from a prior of the plurality of images, determining one or more segments transitioning from an unstable to a stable segment, determining depth for one or more of the one or more segments that have changed by more than the predetermined threshold, determining depth for one or more of the one or more transitioning segments, and combining the determined depth for the one or more unstable segments and the one or more transitioning segments with a predetermined depth of all segments changing less than the predetermined threshold from the prior of the plurality of images.
Abstract:
A method and apparatus for segmenting an image are provided. The method may include the steps of clustering pixels from one of a plurality of images into one or more segments, determining one or more unstable segments changing by more than a predetermined threshold from a prior of the plurality of images, determining one or more segments transitioning from an unstable to a stable segment, determining depth for one or more of the one or more segments that have changed by more than the predetermined threshold, determining depth for one or more of the one or more transitioning segments, and combining the determined depth for the one or more unstable segments and the one or more transitioning segments with a predetermined depth of all segments changing less than the predetermined threshold from the prior of the plurality of images.
Abstract:
A method and system for segmenting a plurality of images. The method comprises the steps of segmenting the image through a novel clustering technique that is, generating a composite depth map including temporally stable segments of the image as well as segments in subsequent images that have changed. These changes may be determined by determining one or more differences between the temporally stable depth map and segments included in one or more subsequent frames. Thereafter, the portions of the one or more subsequent frames that include segments including changes from their corresponding segments in the temporally stable depth map are processed and are combined with the segments from the temporally stable depth map to compute their associated disparities in one or more subsequent frames. The images may include a pair of stereo images acquired through a stereo camera system at a substantially similar time.
Abstract:
A novel disparity computation technique is presented which comprises multiple orthogonal disparity maps, generated from approximately orthogonal decomposition feature spaces, collaboratively generating a composite disparity map. Using an approximately orthogonal feature set extracted from such feature spaces produces an approximately orthogonal set of disparity maps that can be composited together to produce a final disparity map. Various methods for dimensioning scenes and are presented. One approach extracts the top and bottom vertices of a cuboid, along with the set of lines, whose intersections define such points. It then defines a unique box from these two intersections as well as the associated lines. Orthographic projection is then attempted, to recenter the box perspective. This is followed by the extraction of the three-dimensional information that is associated with the box, and finally, the dimensions of the box are computed. The same concepts can apply to hallways, rooms, and any other object.