Patent application number | Description | Published |
20090207235 | Method for Determining Scattered Disparity Fields in Stereo Vision - In a system for stereo vision including two cameras shooting the same scene, a method is performed for determining scattered disparity fields when the epipolar geometry is known, which includes the steps of: capturing, through the two cameras, first and second images of the scene from two different positions; selecting at least one pixel in the first image, the pixel being associated with a point of the scene and the second image containing a point also associated with the above point of the scene; and computing the displacement from the pixel to the point in the second image minimising a cost function, such cost function including a term which depends on the difference between the first and the second image and a term which depends on the distance of the above point in the second image from a epipolar straight line, and a following check whether it belongs to an allowability area around a subset to the epipolar straight line in which the presence of the point is allowed, in order to take into account errors or uncertainties in calibrating the cameras. | 08-20-2009 |
20090304090 | Method for Scalable Video Coding - A method for estimating motion for the scalable video coding, includes the step of estimating the motion field of a sequence of photograms which can be represented with a plurality of space resolution levels including computing the motion field for the minimum resolution level and, until the maximum resolution level is reached, repeating the steps of: rising by one resolution level; extracting the photograms for such resolution level; and computing the motion field for such resolution level. The motion field is computed through an optical flow equation which contains, for every higher level than the minimum resolution level, a regularization factor between levels which points out the difference between the solution for the considered level and the solution for the immediately lower resolution level. A more or less high value of the regularization factor implies more or less relevant changes of the component at the considered resolution during the following process iterations. | 12-10-2009 |
20090304236 | Method of deriving digital terrain models from digital surface models - A method of deriving a digital terrain model from a digital surface model of an area of interest includes: dividing the area of interest into a plurality of area portions or patches; calculating, from the digital surface model, a set of candidate surfaces adapted to represent a ground surface in each area portion; if such set includes at least two candidate surfaces, estimating a distance from the ground surface of each candidate surface by using a function of a set of geometrical features related to the considered candidate surface, such function being derived from a known relation between a digital surface model and the height of the ground surface in a reference area; selecting, as a representation of the ground surface in each area portion, the candidate surface having the smallest distance from the ground surface, so as to obtain local digital terrain models; and merging the different digital terrain models. | 12-10-2009 |
20100215248 | Method for Determining Dense Disparity Fields in Stereo Vision - In a stereo vision system comprising two cameras shooting the same scene from different positions, a method is performed for determining dense disparity fields between digital images shot by the two cameras, including the steps of capturing a first and a second image of the scene, and determining, for each pixel of the second image, the displacement from a point in the first image to such pixel of the second image minimising an optical flow objective function, wherein the optical flow objective function includes, for each pixel of the second image, a term depending in a monotonously increasing way on the distance between the epipolar line associated with such pixel and the above point in the first image, such term depending on calibration parameters of the two cameras and being weighed depending on the uncertainty of the calibration data. | 08-26-2010 |
20110258196 | METHOD AND SYSTEM OF CONTENT RECOMMENDATION - A method of content recommendation, includes: generating a first digital mathematical representation of contents to associate the contents with a first plurality of words describing the contents; generating a second digital mathematical representation of text documents different from the contents to associate the documents with a second plurality of words; processing the first and second pluralities of words to determine a common plurality of words; processing the first and second digital mathematical representations to generate a common digital mathematical representation of the contents and the text documents based on the common plurality of words; and providing content recommendation by processing the common digital mathematical representation. | 10-20-2011 |
20130308861 | METHOD AND SYSTEM FOR COMPARING IMAGES - A method for comparing a first image with a second image. The method identifies first keypoints in the first image and second keypoints in the second image and associates each first keypoint with a corresponding second keypoint to form a corresponding keypoint match. For each pair of first keypoints, the method further calculates the distance therebetween for obtaining a corresponding first length. Similarly, for each pair of second keypoints, the method calculates the distance therebetween for obtaining a corresponding second length. The method further calculates a plurality of distance ratios; each distance ratio is based on a length ratio between a selected one between a first length and a second length and a corresponding selected one between a second length and a first length, respectively. | 11-21-2013 |
20140363078 | METHOD AND SYSTEM FOR IMAGE ANALYSIS - A method for processing an image, including: identifying a group of keypoints in the image; for each keypoint, calculating a corresponding descriptor array including plural array elements, each array element storing values taken by a corresponding color gradient histogram of a respective sub-region of the image in the neighborhood of the keypoint; for each keypoint, subdividing the descriptor array in at least two sub-arrays each including a respective number of elements of the descriptor array, and generating a compressed descriptor array including a corresponding compressed sub-array for each of the at least two sub-arrays, each compressed sub-array obtained by compressing the corresponding sub-array by vector quantization using a respective codebook; exploiting the compressed descriptor arrays of the keypoints for image analysis. For each keypoint of the group, the subdividing is based on correlation relationships among color gradient histograms with values stored in the elements of the descriptor array of each keypoint. | 12-11-2014 |
20150016723 | METHOD AND SYSTEM FOR COMPARING IMAGES - A method comparing first and second images, including: identifying and matching first and second keypoints in the first and second images; arranging a distribution of values of a calculated plurality of first distance ratios in a histogram; determining a number of correct keypoint matches, including: determining a matrix, each matrix element corresponding to a respective pair of keypoint matches with a value corresponding to a difference between a value of the histogram including a distance ratio of the respective pair of keypoint matches and an outlier probability density value weighted by a parameter; determining the parameter value such that the matrix dominant eigenvector is equal to a vector with a first value if the pair of keypoint match is correct and a second value if the pair of keypoint match is incorrect; determining the number of correct keypoint matches based on the dominant eigenvalue associated to the dominant eigenvector. | 01-15-2015 |
20150036936 | IMAGE ANALYSIS - A method for processing an image including: identifying a first group of keypoints in the image; for each keypoint of the first group, identifying at least one corresponding keypoint local feature related to the each keypoint; for the at least one keypoint local feature, calculating a corresponding local feature relevance probability; calculating a keypoint relevance probability based on the local feature relevance probabilities of the at least one local feature; selecting keypoints, among the keypoints of the first group, having the highest keypoint relevance probabilities to form a second group of keypoints, and exploiting the keypoints of the second group for analyzing the image. The local feature relevance probability calculated for a local feature of a keypoint is obtained by comparing the value assumed by the local feature with a corresponding reference statistical distribution of values of the local feature. | 02-05-2015 |