A method includes obtaining two consecutive video frames at a global motion estimation function for execution on a processor, wherein the video frames comprise a current video frame and a previous video frame, and estimating motion between the two consecutive video frames by matching a set of feature points common to both video frames. The set of feature points is maintained by tracking a number of feature points in the current video frame, refreshing the feature points if the number of feature points falls below a refresh threshold, and replenishing the feature points if the number of feature points falls below a replenish threshold. Motion filtering may be performed by buffering a homogenous transformation of the global motion estimation, calculating a geometric mean of the buffered motions, and estimating intentional camera trajectory based on the geometric mean.

A method and an apparatus for extracting a lane line, a device, a computer readable-storage medium and a collection entity are provided. The method includes: obtaining a first group of lane lines of a road based on a first image generated from a point cloud collected by a laser radar; obtaining a second group of lane lines of the road based on a second image collected by a camera; and determining a lane line set of the road based on the first group of lane lines and the second group of lane lines.

An information processing apparatus for processing stereo images of an object includes a disparity calculator to calculate a disparity of the stereo images. The disparity calculator includes an evaluation value calculator to calculate a correlation evaluation value in a search range set for the stereo images; an extreme value detector to detect an extreme value of the correlation evaluation value; a threshold setting unit to set a threshold range for the detected extreme value; a counting unit to count the number of the extreme value existing within the threshold range; and an updating unit to update the set threshold range to a new threshold range when a new extreme value indicating a higher correlation level of the disparity compared to the set threshold range is detected. The counting unit counts the number of the extreme value in a threshold range updated most recently in the search range.

A user may select an image of a scene captured by a mobile device as a reference image. The mobile device may present the reference image as a translucent background image on a display of the mobile device, and may display a preview image of the scene over the translucent background image so that the user can adjust a position and/or an orientation of the mobile device until the preview image is aligned with the translucent background image. In some aspects, the mobile device may determine a similarity value between the preview image and the translucent background image, and may present the similarity value on the display.

An image processing method that includes setting a plurality of search areas of a predetermined size having mutually different circumferential positions along a peripheral edge part and extending in a radial direction from a center of a recess toward the peripheral edge part near the peripheral edge part in an image, executing an edge detection in each search area to obtain detected edge position and edge intensity for each search area, obtaining a relative shift amount for making a degree of similarity of image patterns highest for each search area when another search area adjacent to the search area in the circumferential direction is shifted in the radial direction with respect to the search area, and specifying a position of the boundary in one search area based on the edge positions, the edge intensities and the relative shift amounts in the search area and each of the search areas in neighboring ranges in the circumferential direction.

Subject matter disclosed herein relates to arrangements and techniques that provide for identifying objects within an image such as the face position of a user of a portable electronic device. An application specific integrated circuit (ASIC) is configured to locate objects within images. The ASIC includes an image node configured to process an image and a search node configured to search the image for an object in the image. The ASIC also includes an ensemble node configured to confirm the presence of the object in the image. The ensemble node progressively compares, using computational engines that include accumulators, the pixel values of a template with pixel values of a region of interest in the image to create comparison result values.

Subject matter disclosed herein relates to arrangements and techniques that provide for identifying objects within an image such as the face position of a user of a portable electronic device. An application specific integrated circuit (ASIC) is configured to locate objects within images. The ASIC includes an image node configured to process an image and a search node configured to search the image for an object in the image. The ASIC also includes an ensemble node configured to confirm the presence of the object in the image. The ensemble node compares the pixel values of a template with pixel values of a region of interest in the image to create comparison result values and normalize the comparison result values.

A computerized document bearer authentication system operative in conjunction with a document bearer verifying functionality operative to check at least one aspect of a document bearing individual, the system comprising a computerized document authenticator operative to ascertain that a presented computerized document is valid including reading data from the computerized document and using a processor to find, within the data, validation information useful in ascertaining that the presented computerized document is valid; and a document bearer verifying functionality initiator operative to initiate operation of the document bearer verifying functionality including finding, within the data, bearer verification information useful in checking the at least one aspect and providing the verification information to the document bearer verifying functionality.

For detecting an obstacle with a camera, a first image is viewed by the camera at a first location during a first time. Points on a surface would project onto first pixels of the first image. A second image is viewed by the camera at a second location during a second time. The points on the surface would project onto second pixels of the second image. Coordinates of the second pixels are identified in response to coordinates of the first pixels, in response to a displacement between the first and second locations, and in response to a distance between the camera and the surface. The obstacle is detected in response to whether the first pixels substantially match the second pixels.

A computing device may obtain a first captured image of a scene and a second captured image of the scene. For a plurality of m×n pixel tiles of the first captured image, the computing device may determine respective distance matrixes. The distance matrixes may represent respective fit confidences between the m×n pixel tiles and pluralities of target p×q pixel tiles in the second captured image. The computing device may approximate the distance matrixes with respective bivariate quadratic surfaces. The computing device may upsample the bivariate quadratic surfaces to obtain respective offsets for pixels in the plurality of m×n pixel tiles. The respective offsets, when applied to pixels in the plurality of m×n pixel tiles, may cause parts of the first captured image to estimate locations in the second captured image.