Abstract: A data processing apparatus for determining a pose of an image capturing device based on an image of a three dimensional (3D) scene is disclosed. The data processing apparatus comprises a processing circuitry configured to: select a plurality of key two dimensional (2D) points of a plurality of 2D points of the image based on a respective score of each of the plurality of 2D points; determine at least for a subset of the plurality of 2D points of the image a respective feature vector for obtaining a plurality of feature vectors; concatenate the image with the plurality of feature vectors for obtaining an intermediate tensor; determine a plurality of 3D points of the 3D scene based on the intermediate tensor; and determine the pose based on the plurality of key 2D points of the image and the plurality of 3D points of the 3D scene using a Perspective-n-Point scheme.

Abstract: There is provided a method for estimating a pose of an image in a spatial region and an image processing arrangement. The image processing arrangement is coupled to an imaging capturing arrangement configured to capture one or more 2-D images of a scene within the spatial region. The image processing arrangement is provided with spatial coordinates of a plurality of 3-D point locations within the spatial region. The method includes identifying key features present in 2-D images; identifying a correspondence of clusters of the plurality of 3-D point locations to key feature points present in the 2-D images; and from the identified correspondence, estimating the likely pose of the image processing arrangement relative to the spatial region by using a multi-match likelihood function that finds for each 3-D point location a closest 2-D feature point among k possible 2-D key feature points, where k is an integer greater than one.

Abstract: A computer implemented method of estimating depth for an image and relative camera poses between images in a video sequence, includes backwards warping the source image to generate a first reconstructed target image, and calculating an initial image reconstruction loss based on the target image and the first reconstructed target image. Forward warping the source depth map is performed to generate a second reconstructed target depth map, and an occlusion mask is generated based on the second reconstructed target depth map. The method further includes regularising the initial image reconstruction loss based on the generated occlusion mask. Thus, an occlusion aware method of image reconstruction is provided via a combination of forward and backward warping which identifies and masks occluded areas, and regularizes the image reconstruction loss.

Abstract: A method estimates a camera pose change estimation. The method includes capturing a first image of a scene with a first camera, obtaining a depth map with respect to the first camera based on the first image, capturing a second image of the scene with a second camera. The method also includes obtaining a pose change from the first camera pose to the second camera pose based on the first image and the second image, generating a set of additional pose changes based on the pose change, obtaining a set of reconstructed images and, matching each reconstructed image of the set of reconstructed images with the second image. The method selects a camera pose change estimation from the pose change and the set of additional pose changes that corresponds to a best matching reconstructed image.

Abstract: A focus tunable optical system includes a compound lens, which includes a plurality of focus tunable lenses. Further, the focus tunable optical system comprises a controller, which is configured to shift a focus of the compound lens from a first focal plane to a second focal plane. To this end, the controller is configured to apply, individually to each focus tunable lens of the plurality of the focus tunable lenses, a control signal having a first value for the first focal plane and a second value for the second focal plane.

Abstract: A lane detection system or a vehicle is provided for determining a current lane of a multi-lane road, which the vehicle is driving on. The lane detection system comprises a processing circuitry configured to: obtain a current image of the multi-lane road, i.e. the driving scene; determine a first candidate current lane, i.e. a first estimate of the current lane, by using the leftmost lane in the current image as a first reference lane; determine a second candidate current lane, i.e. a second estimate of the current lane, by using the rightmost lane in the current image of the multi-lane road as a second reference lane; and determine the current lane of the vehicle in the current image of the multi-lane road on the basis of the first candidate current lane and the second candidate current lane.

Abstract: An apparatus for generating a model for pose estimation of a system obtains training data for a multiple locations. The training data includes one or more images captured by an image capturing device and the respective poses of the captured images. At least one data sample is generated from the training data for each of the captured images, where a data sample for an image is an assignment of the image and at least one other image selected from the training data to respective poses. A neural network is trained with a data set made up of the data samples to estimate a respective pose of a localization image from: the localization image; at least one additional image from the training data; and a respective pose of each of additional image.

Abstract: A focus tunable optical system includes a compound lens, which includes a plurality of focus tunable lenses. Further, the focus tunable optical system comprises a controller, which is configured to shift a focus of the compound lens from a first focal plane to a second focal plane. To this end, the controller is configured to apply, individually to each focus tunable lens of the plurality of the focus tunable lenses, a control signal having a first value for the first focal plane and a second value for the second focal plane.

Abstract: A driver assistance system detects lane markings in a perspective image of a road in front of a vehicle. The driver assistance system extracts a plurality of features, in particular lane markings, from the perspective image for generating a set of feature coordinates, in particular lane marking coordinates. The system generates a plurality of pairs of feature coordinates, each pair defining a straight line, and estimates a lane curvature on the basis of a subset of the pairs of feature coordinates. For each pair a straight line defined by the pair intersects a predefined target portion of the perspective image, the predefined target portion including a plurality of possible positions of a vanishing point.

Abstract: A focus tunable optical system includes a compound lens, which includes a plurality of focus tunable lenses. Further, the focus tunable optical system includes a controller, which is configured to shift a focus of the compound lens from a first focal plane to a second focal plane. To this end, the controller is configured to apply, individually to each focus tunable lens of the plurality of the focus tunable lenses, a control signal having a first value for the first focal plane and a second value for the second focal plane.

Abstract: The invention relates to an image processing apparatus for generating an HDR image associated with a first view on the basis of a plurality of LDR images, including a first LDR image and a second LDR image. The first LDR image is associated with the first view and a first exposure, i.e. a first dynamic range, and the second LDR image is associated with a second view and a second exposure, i.e. a second dynamic range. The image processing apparatus comprises a processor configured to provide a neural network having a plurality of neural subnetworks including a first neural subnetwork. The first neural subnetwork is configured to generate the HDR image on the basis of: (i) the first LDR image, (ii) the second LDR image, and (iii) a modified first LDR image. The modified first LDR image is associated with the first view and the second exposure.

Abstract: A method and an apparatus for generating a High Dynamic Range, HDR, image are proposed. The method comprises obtaining a set of two or more input images, the two or more input images including a reference image and one or more non-reference images; for each of the one or more non-reference images, performing an image analysis which comprises, for each region of a plurality of regions of the non-reference image, assessing whether the region of the non-reference image and a corresponding region of the reference image show the same image content and declaring the region of the non-reference image as valid or as invalid based on the assessment; and generating the HDR image by fusing the reference image and the one or more non-reference images, wherein the fusing comprises, for each of the one or more non-reference images, disregarding the invalid regions of the respective non-reference image.

Abstract: A focus tunable optical system includes a compound lens, which includes a plurality of focus tunable lenses. Further, the focus tunable optical system includes a controller, which is configured to shift a focus of the compound lens from a first focal plane to a second focal plane. To this end, the controller is configured to apply, individually to each focus tunable lens of the plurality of the focus tunable lenses, a control signal having a first value for the first focal plane and a second value for the second focal plane.

Abstract: The disclosure relates to an image processing apparatus for determining a depth of a pixel of a reference image of a plurality of images representing a visual scene relative to a plurality of locations, wherein the plurality of locations define a two-dimensional grid with rows and columns and wherein the location of the reference image is associated with a reference row and a reference column of the grid. The image processing apparatus comprises a depth determiner configured to determine a first depth estimate on the basis of the reference image and a first subset of the plurality of images for determining the depth of the pixel of the reference image, wherein the images of the first subset are associated with locations being associated with a row of the grid different than the reference row and with a column of the grid different than the reference column.

Abstract: An image processing device for generating an output image front an input image of a scene, the input image being the first image and the output image being the second image, the output image corresponds to an exposure that is different from an exposure of the input image, the image processing device comprising an intensity transformer that is configured to determine one or more intensities of an output pixel of the output image based on an input patch around an input pixel of the input image that corresponds to the output pixel.

Abstract: An advanced driver assistance system is configured to detect lane markings in a perspective image of a road in front of the vehicle. The perspective image of the road is separated into horizontal stripes corresponding to different road portions at different average distances from the vehicle. Features are extracted from the plurality of horizontal stripes using a plurality of kernels.

Abstract: The disclosure proposes a method for obtaining a High Dynamic Range (HDR) image. The method comprises storing a main set of selectable exposure times and a plurality of candidate reduced sets being respective subsets of the main set, controlling a capture of calibration images at respectively each exposure time of the main set, for each candidate reduced set, selecting the calibration images captured with the exposure times of the candidate reduced set and computing a score value depending on intensities of the selected calibration images, selecting a candidate reduced set from the candidate reduced sets on the basis of the computed score values, and controlling the capture of the plurality of images at respectively each exposure time of the selected candidate reduced set for obtaining the HDR image.

Abstract: The invention relates to an image processing apparatus for generating an HDR image associated with a first view on the basis of a plurality of LDR images, including a first LDR image and a second LDR image. The first LDR image is associated with the first view and a first exposure, i.e. a first dynamic range, and the second LDR image is associated with a second view and a second exposure, i.e. a second dynamic range. The image processing apparatus comprises a processor configured to provide a neural network having a plurality of neural subnetworks including a first neural subnetwork. The first neural subnetwork is configured to generate the HDR image on the basis of: (i) the first LDR image, (ii) the second LDR image, and (iii) a modified first LDR image. The modified first LDR image is associated with the first view and the second exposure.

Abstract: A driver assistance system detects lane markings in a perspective image of a road in front of a vehicle. The driver assistance system extracts a plurality of features, in particular lane markings, from the perspective image for generating a set of feature coordinates, in particular lane marking coordinates. The system generates a plurality of pairs of feature coordinates, each pair defining a straight line, and estimates a lane curvature on the basis of a subset of the pairs of feature coordinates. For each pair a straight line defined by the pair intersects a predefined target portion of the perspective image, the predefined target portion including a plurality of possible positions of a vanishing point.

Abstract: A method and an apparatus for generating a High Dynamic Range, HDR, image are proposed. The method comprises obtaining a set of two or more input images, the two or more input images including a reference image and one or more non-reference images; for each of the one or more non-reference images, performing an image analysis which comprises, for each region of a plurality of regions of the non-reference image, assessing whether the region of the non-reference image and a corresponding region of the reference image show the same image content and declaring the region of the non-reference image as valid or as invalid based on the assessment; and generating the HDR image by fusing the reference image and the one or more non-reference images, wherein the fusing comprises, for each of the one or more non-reference images, disregarding the invalid regions of the respective non-reference image.