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 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 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: 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 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 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.