Abstract: A stroke detection apparatus for determining that a stroke is occurring or has recently occurred to a user, wherein the apparatus comprises a data processing device comprising a processor and at least one wearable sensor configured to be worn by a user and configured to transmit a movement data of the user to the data processing device. The data processing device is configured to process the movement data to determine a first probability of a user stroke over a first time period and a second probability of a user stroke over a second time period. A stroke detection signal is then generated in dependence on at least the first probability and second probability.

Abstract: A method and arrangement for calibrating stereo cameras. A first image from a first camera is received, and a second image is received from a second camera, the first image and the second image comprise an overlap. One or more candidate points of the first image and of the second image are determined in the overlap. The candidate points of the first image are matched with the candidate points of the second image and pairs of corresponding candidate points are determined. A homography of the first camera is calculated based on the pairs of corresponding candidate points and a homography of the second camera is calculated based on the pairs of corresponding candidate points. The first camera and the second camera are calibrated by adjusting an intrinsic parameter or an extrinsic parameter of each respective camera, based on the calculated homography of each respective camera.

Abstract: The disclosure relates to a section of a wind turbine rotor blade, the section comprising: three or more wing members extending along each other, at a distance from each other, and along a longitudinal direction of the wind turbine rotor blade, wherein at least one, and preferably each, wing member has an airfoil shaped cross-section as seen in a plane transverse to the longitudinal extension of the wing member, wherein each wing member extends from a respective inner end to a respective outer end, wherein the section further comprises a first plurality of three or more struts and a second plurality of three or more struts, wherein the struts in the first plurality of struts each extend from an inner end of one wing member to an inner end of another wing member, such that the struts in the first plurality of struts interconnect the wing members at their inner ends, and wherein the struts in the second plurality of struts each extend from an outer end of one wing member to an outer end of another wing member,

Abstract: A blade (104) for a rotor of a wind turbine is provided. The blade (104) comprises: a truss-like three-dimensional structure having strut members (108; 110; 112) forming the truss-like structure, wherein a plurality of the strut members (108; 110; 112) in the truss-like structure have an airfoil-shaped cross-section.

Abstract: An apparatus being adapted to determine an occupancy in a designated area, said apparatus comprising a memory and a controller, said controller being configured to determine at least one passage time; wherein said passage time is a time for a detected passage into and/or out of said area based on said image stream, determine an average occupancy time, determine if a passage into said designated area is estimated to occupy the designated area by comparing the time for the passage with the average occupancy time, and determine an estimation of the present occupancy in the designated area to equal the number of such passages.

Abstract: The disclosure relates to a rotor blade (104) for a wind turbine, the rotor blade (104) comprising two or more wing members (110, 112, 114), wherein each wing member has an airfoil shaped cross-section as seen in a plane transverse to the longitudinal extension of the wing member, wherein each wing member (110, 112, 114) is divided into at least a first sub-member (110a) and a second sub-member (110b), the sub-members (110a-b) being arranged one after another along a longitudinal direction of the rotor blade (104), wherein, in each wing member (110, 112, 114), at an interface (116) between the first and the second sub-member (110a-b), the first sub-member (110a) is arranged in the rotor blade (104) with an outer end angular orientation about the longitudinal direction and the second sub-member (110b) is arranged in the rotor blade (104) with an inner end angular orientation about the longitudinal direction, the inner end angular orientation of the second sub-member (110b) being different from the outer end an

Abstract: A method and arrangement for calibrating stereo cameras in a vehicle is disclosed. A first image from a first camera is received, and a second image is received from a second camera, the first image and the second image comprise an overlap. One or more candidate points of the first image and of the second image are determined in the overlap. The candidate points of the first image are matched with the candidate points of the second image and pairs of corresponding candidate points are determined. A homography of the first camera is calculated based on the pairs of corresponding candidate points and a homography of the second camera is calculated based on the pairs of corresponding candidate points. The first camera and the second camera are calibrated by adjusting an intrinsic parameter or an extrinsic parameter of each respective camera, based on the calculated homography of each respective camera.

Abstract: A blade (104) for a rotor of a wind turbine is provided. The blade (104) comprises: a truss-like three-dimensional structure having strut members (108; 110; 112) forming the truss-like structure, wherein a plurality of the strut members (108; 110; 112) in the truss-like structure have an airfoil-shaped cross-section.

Abstract: An apparatus being adapted to determine an occupancy in a designated area, said apparatus comprising a memory and a controller, said controller being configured to determine at least one passage time; wherein said passage time is a time for a detected passage into and/or out of said area based on said image stream, determine an average occupancy time, determine if a passage into said designated area is estimated to occupy the designated area by comparing the time for the passage with the average occupancy time, and determine an estimation of the present occupancy in the designated area to equal the number of such passages.

Abstract: A method for tracking objects in a scene being viewed by a sequence of digital images comprises: separating a region of interest in the digital images into a plurality of spatially smaller, overlapping modules, and defining a hidden Markov model for each module. The method further comprises observing detections of positions of possible objects at different times, considering a set of states at a point of time (t1) such that the set of states comprises a state having a global optimum probability, and backtracking through the sequence of digital images for each hidden Markov model to shrink the set of states that are possible for earlier parts of the sequence of digital images, such that a single optimal state is found for an earlier point of time (t2<t1), whereby tracks of detected objects through the scene are determined up to the earlier point of time (t2).

Abstract: A device for converting wind energy into a reciprocating motion. The device has a sail that extends in a main wind direction and pivotally oscillates when subjected to wind. The sail is connected to a first support that is configured to move in a first direction when the sail during its oscillation moves towards any of two outermost positions from a neutral position, and move in a second direction opposite the first direction when the sail during its oscillation moves towards its neutral position from any of its outermost positions, thereby creating a reciprocating motion of the first support when the sail is subjected to the wind. A further device, a method and a system are also described.

Abstract: A method, apparatus and computer readable medium for automatically recognizing a human face, which are adapted to: retrieve an image of the face; extract a number of feature patches from the image of the face; calculate a feature value for each feature patch, as a function of an image-derivate of the respective feature patch; and comparing the feature values with corresponding feature values of a number of feature patches of a reference image stored in an image database, for determining a recognition of the human face.

Abstract: Character recognition includes detecting a union of characters, preprocessing the union of characters, comparing the preprocessed union of characters with one or more template symbols, and applying a decision rule to either reject a template symbol or decide that the template symbol is included in the union of characters. Such preprocessing involves representing the union of characters as one or more curves, and parameterizing the curve(s); and, regarding various classes of transformation, forming one or more shapes for the curve(s). The comparing operation involves forming one or more geometric proximity measures, and determining for every shape the values of those measures between the shape and correspondingly determined shapes for the template symbols. Applying a decision rule involves selecting one or more template symbols in consideration of the values.

Abstract: A method for tracking objects in a scene being viewed by a sequence of digital images comprises: separating a region of interest in the digital images into a plurality of spatially smaller, overlapping modules, and defining a hidden Markov model for each module. The method further comprises observing detections of positions of possible objects at different times, considering a set of states at a point of time (t1) such that the set of states comprises a state having a global optimum probability, and backtracking through the sequence of digital images for each hidden Markov model to shrink the set of states that are possible for earlier parts of the sequence of digital images, such that a single optimal state is found for an earlier point of time (t2<t1), whereby tracks of detected objects through the scene are determined up to the earlier point of time (t2).

Abstract: Character recognition includes detecting a union of characters, preprocessing the union of characters, comparing the preprocessed union of characters with one or more template symbols, and applying a decision rule to either reject a template symbol or decide that the template symbol is included in the union of characters. Such preprocessing involves representing the union of characters as one or more curves, and parameterizing the curve(s); and, regarding various classes of transformation, forming one or more shapes for the curve(s). The comparing operation involves forming one or more geometric proximity measures, and determining for every shape the values of those measures between the shape and correspondingly determined shapes for the template symbols. Applying a decision rule involves selecting one or more template symbols in consideration of the values.

Abstract: A method of character recognition includes detecting a union of characters, preprocessing the union of characters, comparing the preprocessed union of characters with one or more template symbols, and applying a decision rule in order to either reject a template symbol or decide that the template symbol is included in the union of characters. Preprocessing the union of characters involves representing the union of characters as one or more curves, and parameterising said curve or curves, and regarding various classes of transformations forming one or more shapes for the curve or curves. The comparing operation involves forming one or more geometric proximity measures, and determining for every shape the values of said geometric proximity measures between said shape and correspondingly determined shapes for the template symbols. Finally, applying a decision rule involves selecting one or more template symbols in consideration of the values.

Abstract: A method of character recognition includes detecting a union of characters, preprocessing the union of characters, comparing the preprocessed union of characters with one or more template symbols, and applying a decision rule in order to either reject a template symbol or decide that the template symbol is included in the union of characters. Preprocessing the union of characters involves representing the union of characters as one or more curves, and parameterizing said curve or curves, and regarding various classes of transformation forming one or more shapes for the curve or curves. The comparing operation involves forming one or more geometric proximity measures, and determining for every shape the values of said geometric proximity measures between said shape and correspondingly determined shapes for the template symbols. Finally, applying a decision rule involves selecting one or more template symbols in consideration of the values.