Abstract: The invention relates to a computer-implemented segmentation method of an image comprising a segmentation by watershed applied to an evaluation of a curvature at pixels of the image.

Abstract: Described herein is a method of calibrating a three-dimensional imaging system. During calibration, a position and an orientation of the three-dimensional imaging system is determined with respect to a first parameter comprising a real world vertical direction (Vw) and to a second parameter comprising an origin of a three-dimensional scene captured by the imaging system. The first and second parameters are used to derive a calibration matrix (MC2w) which is used to convert measurements from a virtual coordinate system (Mc) of the three-dimensional imaging system into a real coordinate system (Mw) related to the real world. The calibration matrix (MC2w) is used to rectify measurements prior to signal processing. An inverse calibration matrix (Mw2c) is also determined. Continuous monitoring and adjustment of the setup of the three-dimensional imaging system is carried out and the calibration matrix (Mc2w) and its inverse (Mw2c) are adjusted accordingly.

Abstract: The present invention relates to a method for stabilizing a series of measurements of a physical variable captured by a digital sensor. This method comprises the steps of: capturing at least a first measurement, a second measurement, and a third measurement of said physical variable and storing each measurement in a digital memory. The first and second measurements are compared and, if a difference between the first measurement and the second measurement is below a predetermined threshold, the second measurement is replaced in the memory by a corrected second measurement where the difference with respect to said first measurement has been reduced using a first filtering strength.

Abstract: Described herein is a method for recognizing a human head in a source image. The method comprises detecting a contour of at least part of a human body in the source image, calculating a depth of the human body in the source image. From the source image, a major radius size and a minor radius size of an ellipse corresponding to a human head at the depth is calculated, and, for at least several of a set of pixels of the detected contour, generating in an accumulator array at least one segment of an ellipse centered on the position of the contour pixel and having the major and minor radius sizes. Positions of local intensity maxima in the accumulator array are selected as corresponding to positions of the human head candidates in the source image.

Abstract: Described herein is a user interface that provides contextual feedback, controls and interface elements on a display screen of an interactive three-dimensional imaging system. A user interacts with the interface to provide control signals in accordance with those recognized by the system to a makes use of at least one POI in a three-dimensional scene that is imaged by the imaging system to provide control signals for the user interface. Control signals are provided by means of gestures which are analyzed in real-time by gesture recognition processes that analyze statistical and geometrical properties of POI motion and trajectories.

Abstract: Described herein is a method of calibrating a three-dimensional imaging system. During calibration, a position and an orientation of the three-dimensional imaging system is determined with respect to a first parameter comprising a real world vertical direction (Vw) and to a second parameter comprising an origin of a three-dimensional scene captured by the imaging system. The first and second parameters are used to derive a calibration matrix (MC2w) which is used to convert measurements from a virtual coordinate system (Mc) of the three-dimensional imaging system into a real coordinate system (Mw) related to the real world. The calibration matrix (MC2w) is used to rectify measurements prior to signal processing. An inverse calibration matrix (Mw2c) is also determined. Continuous monitoring and adjustment of the setup of the three-dimensional imaging system is carried out and the calibration matrix (Mc2w) and its inverse (Mw2c) are adjusted accordingly.

Abstract: The present invention relates to a method for tracking at least one object in a sequence of frames, each frame comprising a pixel array, wherein a depth value is associated to each pixel. The method comprises grouping at least some of said pixels of each frame into several regions, grouping said regions into clusters (B1, . . . , B5) of interconnected regions; and determining that a cluster (B2, . . . , B5) which is adjacent to another cluster (B1) in a two-dimensional projection belongs to an object partially occluded by said other cluster (B1) if it has a different depth value than said other cluster (B1).

Abstract: Described herein is a user interface that provides contextual feedback, controls and interface elements on a display screen of an interactive three-dimensional imaging system. A user interacts with the interface to provide control signals in accordance with those recognised by the system to a makes use of at least one POI in a three-dimensional scene that is imaged by the imaging system to provide control signals for the user interface. Control signals are provided by means of gestures which are analysed in real-time by gesture recognition processes that analyse statistical and geometrical properties of POI motion and trajectories.

Abstract: The present invention relates to a method for stabilising a series of measurements of a physical variable captured by a digital sensor. This method comprises the steps of: capturing at least a first measurement, a second measurement, and a third measurement of said physical variable and storing each measurement in a digital memory. The first and second measurements are compared and, if a difference between the first measurement and the second measurement is below a predetermined threshold, the second measurement is replaced in the memory by a corrected second measurement where the difference with respect to said first measurement has been reduced using a first filtering strength.

Abstract: Described herein is a method for recognising a human head in a source image. The method comprises detecting a contour of at least part of a human body in the source image, calculating a depth of the human body in the source image. From the source image, a major radius size and a minor radius size of an ellipse corresponding to a human head at the depth is calculated, and, for at least several of a set of pixels of the detected contour, generating in an accumulator array at least one segment of an ellipse centred on the position of the contour pixel and having the major and minor radius sizes. Positions of local intensity maxima in the accumulator array are selected as corresponding to positions of the human head candidates in the source image.

Abstract: The present invention relates to a method for tracking at least one object in a sequence of frames, each frame comprising a pixel array, wherein a depth value is associated to each pixel. The method comprises grouping at least some of said pixels of each frame into several regions, grouping said regions into clusters (B1, . . . , B5) of interconnected regions; and determining that a cluster (B2, . . . , B5) which is adjacent to another cluster (B1) in a two-dimensional projection belongs to an object partially occluded by said other cluster (B1) if it has a different depth value than said other cluster (B1).

Abstract: The present invention relates to a volume recognition method comprising the steps of: a) capturing three-dimensional image data using a 3D imaging system 3, wherein said image data represent a plurality of points 5, each point 5 having at least a set of coordinates in a three-dimensional space; b) grouping at least some of the points 5 in a set of clusters 6; c) selecting, according to a first set of parameters such as position and size, a cluster 6 corresponding to an object of interest 1 located in range of said imaging system 3; d) grouping at least some of the points 5 of the selected cluster 6 in a set of sub-clusters according to a second set of parameters comprising their positions in the three-dimensional space, wherein each sub-cluster has a centroid 11 in the three-dimensional space; and e) associating a volume 12 to each of at least some of said sub-clusters, wherein said volume 12 is fixed to the centroid 11 of said sub-cluster.

Abstract: The present invention relates to a volume recognition method comprising the steps of: a) capturing three-dimensional image data using a 3D imaging system 3, wherein said image data represent a plurality of points 5, each point 5 having at least a set of coordinates in a three-dimensional space; b) grouping at least some of the points 5 in a set of clusters 6; c) selecting, according to a first set of parameters such as position and size, a cluster 6 corresponding to an object of interest 1 located in range of said imaging system 3; d) grouping at least some of the points 5 of the selected cluster 6 in a set of sub-clusters according to a second set of parameters comprising their positions in the three-dimensional space, wherein each sub-cluster has a centroid 11 in the three-dimensional space; and e) associating a volume 12 to each of at least some of said sub-clusters, wherein said volume 12 is fixed to the centroid 11 of said sub-cluster.