Abstract: Described herein is a method for signal processing in which noise in an input signal comprising an intensity which is a function of at least a first coordinate and a second coordinate. A noise reduction or de-noising process is applied to the input signal in respect of the first coordinate to generate an intermediate de-noised signal. A second noise reduction or de-noising process is applied to the intermediate de-noised signal in respect of the second coordinate to generate an output de-noised signal. For each coordinate, noise reduction processes are applied in two directions, the results of these processes being averaged to provide the de-noised signals. Weighting is applied in accordance with the detection of an edge within the signal used as input in the de-noising process.

Abstract: Described herein is a method for enabling human-to-computer three-dimensional hand gesture-based natural interactions from depth images provided by a range finding imaging system. The method enables recognition of simultaneous gestures from detection, tracking and analysis of singular points of interests on a single hand of a user and provides contextual feedback information to the user. The singular points of interest of the hand: include hand tip(s), fingertip(s), palm center and center of mass of the hand, and are used for defining at least one representation of a pointer. The point(s) of interest is/are tracked over time and are analyzed to enable the determination of sequential and/or simultaneous “pointing” and “activation” gestures performed by a single hand.

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: Described herein is a method for correcting defective depth values in depth map images. Defective values correspond to “noisy pixels” located on continuous flat surfaces and interpolated “flying pixels” located along an edge between a foreground object and a background object. The method comprising the steps of accessing a depth map of a scene which includes the foreground and background objects, detecting and identifying noisy and interpolated depth measurements within the depth map using a method, defining and applying a correction to each of the detected defective noisy and interpolated depth measurements using a specifically defined weighted correction factor. By providing the corrected defective depth values in depth map images, edges are sharpened in depth and continuous surfaces are flattened, enabling higher efficiency and robustness of further image processing.

Abstract: Described herein is a wireless remote control device (100) which can be used on the hand (150) of a user to provide both hardware-based control signals which can be associated with gesture-based control signals for enhanced gesture recognition systems. The device (100) comprises a housing (110) having a sensing unit having at least one control button (120, 130, 140) which is capable of generating a control signal for an associated computerized system. A computerized system utilizes information obtained from the control device (100) together with information obtained from a gesture recognition system to resolve any ambiguities due to, for example, occlusion of the hand performing the gesture or the hand being outside the field of view of an imaging system associated with the computerized system, and to trigger interactions within the gesture based interaction system.

Abstract: Described herein is a method for enabling human-to-computer three-dimensional hand gesture-based natural interactions. From depth images provided by a range finding imaging system, the method enables efficient and robust detection of a particular sequence of natural gestures including a beginning (start), and an ending (stop) of a predetermined type of natural gestures for delimiting the period during which a control (interaction) gesture is operating in an environment wherein a user is freely moving his hands. The invention is more particularly, although not exclusively, concerned by detection without any false positives nor delay, of intentionally performed natural gesture subsequent to a starting finger tip or hand tip based natural gesture so as to provide efficient and robust navigation, zooming and scrolling interactions within a graphical user interface up until the ending finger tip or hand tip based natural gesture is detected.

Abstract: Described herein is a method and system for marker-less three-dimensional modelling, fitting and tracking of a skeletal representation of an object in a three-dimensional point cloud. In particular, it concerns the tracking of a human user skeletal representation with respect to time. The method comprises inputting a three-dimensional point cloud derived from a depth map; predetermining a set of control points representing the skeleton of the user, determining a start-up skeleton pose, obtaining an orthographic representation of the user 3D point cloud projected onto a grid by sampling the 3D point cloud with a predetermined static size, determining a set of curvature centers points approximating central axes of main parts of the user, determining the torso plane, and refining and/or defining the principal direction of the body.

Abstract: Described herein is a method for detecting, identifying and tracking hand, hand parts, and fingers on the hand (500) of a user within depth images of a three-dimensional scene. Arms of a user are detected, identified, segmented from the background of the depth images, and tracked with respect to time. Hands of the user are identified and tracked and the location and orientation of its parts, including the palm and the fingers (510, 520, 530, 540, 550) are determined and tracked in order to produce output information enabling gesture interactions.

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: Described herein is a method for enabling human-to-computer three-dimensional hand gesture-based natural interactions from depth images provided by a range finding imaging system. The method enables recognition of simultaneous gestures from detection, tracking and analysis of singular points of interests on a single hand of a user and provides contextual feedback information to the user. The singular points of interest of the hand: include hand tip(s), fingertip(s), palm centre and centre of mass of the hand, and are used for defining at least one representation of a pointer. The point(s) of interest is/are tracked over time and are analysed to enable the determination of sequential and/or simultaneous “pointing” and “activation” gestures performed by a single hand.

Abstract: Described herein is a method for detecting, identifying and tracking hand, hand parts, and fingers on the hand (500) of a user within depth images of a three-dimensional scene. Arms of a user are detected, identified, segmented from the background of the depth images, and tracked with respect to time. Hands of the user are identified and tracked and the location and orientation of its parts, including the palm and the fingers (510, 520, 530, 540, 550) are determined and tracked in order to produce output information enabling gesture interactions.

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 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.