Abstract: An enhanced object detecting method and apparatus is presented. A plurality of successive frames is captured by a monocular camera and the image data of the captured frames are transformed with respect to a predetermined point of view. For instance, the images may be transformed in order to obtain a top-down view. Particular features such as lines are extracted from the transformed image data, and corresponding features of successive frames are matched. An angular change of corresponding features is determined and boundaries of an object are identified based on the angular change of the features.

Abstract: An image recognition system and method for a vehicle, including at least two camera units, each being configured to record an image of a road in the vicinity of the vehicle and to provide image data representing the respective image of the road, a first image processor configured to combine the image data provided by the at least two camera units into a first top-view image. The first top-view image is aligned to a road image plane, a first feature extractor configured to extract lines from the first top-view image, a second feature extractor configured to extract an optical flow from the first top-view image and a second top-view image, generated before the first top-view image by the first image processor, and a curb detector configured to detect curbs in the road based on the extracted lines and the extracted optical flow and provide curb data representing the detected curbs.

Abstract: An enhanced object detecting method and apparatus is presented. A plurality of successive frames is captured by a monocular camera and the image data of the captured frames are transformed with respect to a predetermined point of view. For instance, the images may be transformed in order to obtain a top-down view. Particular features such as lines are extracted from the transformed image data, and corresponding features of successive frames are matched. An angular change of corresponding features is determined and boundaries of an object are identified based on the angular change of the features.

Abstract: An image recognition system and method for a vehicle, including at least two camera units, each being configured to record an image of a road in the vicinity of the vehicle and to provide image data representing the respective image of the road, a first image processor configured to combine the image data provided by the at least two camera units into a first top-view image. The first top-view image is aligned to a road image plane, a first feature extractor configured to extract lines from the first top-view image, a second feature extractor configured to extract an optical flow from the first top-view image and a second top-view image, generated before the first top-view image by the first image processor, and a kerb detector configured to detect kerbs in the road based on the extracted lines and the extracted optical flow and provide kerb data representing the detected kerbs.

Abstract: A method for estimating ego motion of an object moving on a surface, the method including generating at least two composite top view images of the surface on the basis of video frames provided by at least one onboard video camera of the object moving on the surface; performing a region matching between consecutive top view images to extract global motion parameters of the moving object; calculating the ego motion of the moving object from the extracted global motion parameters of the moving object.

Abstract: A method for estimating ego motion of an object moving on a surface, the method including generating at least two composite top view images of the surface on the basis of video frames provided by at least one onboard video camera of the object moving on the surface; performing a region matching between consecutive top view images to extract global motion parameters of the moving object; calculating the ego motion of the moving object from the extracted global motion parameters of the moving object.

Abstract: A method of detecting a geometrically transformed object in an image comprises comparing a template comprising a plurality of line segments for the object with regions of an image, and determining a similarity measure that uses a statistical measure based on the sums of pixel values of line segments of the image corresponding to each of the line segments of the template. Embodiments of the invention use a discrete set of geometrically transformed versions of the template, for example using the similarity transform.

Abstract: Blurred image data is sharpened by converting three channels of RGB data into a single channel of intensity data, processing the intensity data to generate integral image data, applying a variable size filter to the integral image data to generate box-filtered data, calculating a gain factor for each pixel position in dependence upon the box-filtered data, the intensity data and the size of the filter used for that pixel position, and multiplying the original RGB data of each pixel by the gain factor for that pixel to generate sharpened RGB data. The size of the filter is selected at each pixel position in dependence upon an estimate of the local amount of blur. In this way, as the amount of blur changes, the filter size changes appropriately. By processing the integral image data to generate box-filtered data, a constant number of processing operations are required for image sharpening irrespective of the size of filter that is used.

Abstract: A method of estimating a transformation between a pair of images, comprises estimating local transformations for a plurality of regions of the images to derive a set of estimated transformations, and selecting a subset of said estimated local transformations as estimated global transformations for the image.

Abstract: Blurred image data is sharpened by converting three channels of RGB data into a single channel of intensity data, processing the intensity data to generate integral image data, applying a variable size filter to the integral image data to generate box-filtered data, calculating a gain factor for each pixel position in dependence upon the box-filtered data, the intensity data and the size of the filter used for that pixel position, and multiplying the original RGB data of each pixel by the gain factor for that pixel to generate sharpened RGB data. The size of the filter is selected at each pixel position in dependence upon an estimate of the local amount of blur. In this way, as the amount of blur changes, the filter size changes appropriately. By processing the integral image data to generate box-filtered data, a constant number of processing operations are required for image sharpening irrespective of the size of filter that is used.

Abstract: A method of representing a 2-dimensional image comprises deriving at least one 1-dimensional representation of the image by projecting the image onto at least one axis, and applying a Fourier transform to said 1-dimensional representation. The representation can be used for estimation of dominant motion between images.

Abstract: A method of detecting a geometrically transformed object in an image comprises comparing a template comprising a plurality of line segments for the object with regions of an image, and determining a similarity measure that uses a statistical measure based on the sums of pixel values of line segments of the image corresponding to each of the line segments of the template. Embodiments of the invention use a discrete set of geometrically transformed versions of the template, for example using the similarity transform.

Abstract: There is described a method of processing a plurality of images to determine one or more groups of images with each group of images forming a panorama. The method comprises identifying distinctive features in each image, comparing a distinctive feature in one image with distinctive features in other images to identify possible matching features, and processing said possible matches to determine said one or more groups of images. When comparing distinctive features, a distinctive feature in one image is only compared with a subset of the distinctive features in the other images which satisfy one or more predefined criteria. The criteria could involve the similarity of the images, or alternatively whether or not a decision on registration has already been made for the pair of images concerned, hi this way, the number of feature comparisons is reduced.

Abstract: A method of representing an image comprises deriving at least one 1-dimensional representation of the image by projecting the image onto an axis, wherein the projection involves summing values of selected pixels in a respective line of the image perpendicular to said axis, characterised in that the number of selected pixels is less than the number of pixels in the line.

Abstract: A method of detecting an object, in particular a face, in an image using template matching uses at least two different templates for the same object. Templates are provided for left eye, right eye and between-the-eyes. A confidence map is produced for each template and the confidence maps are merged. This may take place at several resolutions. The detected regions are further checked with symmetry, texture and/or geometrical relationship to other facial parts.

Abstract: A method of detecting an object in an image comprises comparing a template with a region of an image and determining a similarity measure, wherein the similarity measure is determined using a statistical measure. The template comprises a number of regions corresponding to parts of the object and their spatial relations. The variance of the pixels within the total template is set in relation to the variances of the pixels in all individual regions, to provide a similarity measure.

Abstract: A method of estimating a transformation between a pair of images, comprises estimating local transformations for a plurality of regions of the images to derive a set of estimated transformations, and selecting a subset of said estimated local transformations as estimated global transformations for the image.

Abstract: A method of representing a 2-dimensional image comprises deriving at least one 1-dimensional representation of the image by projecting the image onto at least one axis, and applying a Fourier transform to said 1-dimensional representation. The representation can be used for estimation of dominant motion between images.